Serialized Form (Cognitive Foundry)

Package gov.sandia.cognition.algorithm
- Class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm extends AbstractIterativeAlgorithm implements Serializable
  - Serialized Fields
    - maxIterations
```
int maxIterations
```
      Maximum number of iterations before stopping
- Class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - iteration
```
int iteration
```
      Number of iterations the algorithm has executed.
- Class gov.sandia.cognition.algorithm.AbstractParallelAlgorithm extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper extends AbstractIterativeAlgorithm implements Serializable
  - Serialization Methods
    - readResolve
```
protected java.lang.Object readResolve()
```
      This method is detected by the Java Serialization code and is called on deserialization. It allows the object to deal with transient values.
  - Serialized Fields
    - algorithm
```
AnytimeAlgorithm<ResultType> algorithm
```
      Underlying algorithm to wrap.
Package gov.sandia.cognition.algorithm.event
- Class gov.sandia.cognition.algorithm.event.AbstractIterativeAlgorithmListener extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.algorithm.event.IterationMeasurablePerformanceReporter extends AbstractIterativeAlgorithmListener implements Serializable
  - Serialized Fields
    - out
```
java.io.PrintStream out
```
      The print stream to report performance to.
    - format
```
java.lang.String format
```
      The format for the performance report, passed to String.format.
- Class gov.sandia.cognition.algorithm.event.IterationStartReporter extends AbstractIterativeAlgorithmListener implements Serializable
  - Serialized Fields
    - out
```
java.io.PrintStream out
```
      The print stream to report performance to.
    - format
```
java.lang.String format
```
      The format for the performance report, passed to String.format.
Package gov.sandia.cognition.collection
- Class gov.sandia.cognition.collection.AbstractLogNumberMap extends AbstractScalarMap<KeyType,LogNumber> implements Serializable
- Class gov.sandia.cognition.collection.AbstractMutableDoubleMap extends AbstractScalarMap<KeyType,MutableDouble> implements Serializable
- Class gov.sandia.cognition.collection.AbstractScalarMap extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - map
```
java.util.Map<K,V> map
```
      Map backing that performs the storage.
- Class gov.sandia.cognition.collection.DefaultComparator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.collection.DefaultIndexer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - valueList
```
java.util.ArrayList<E> valueList
```
      The list of values, which can be accessed by index.
    - valueToIndexMap
```
java.util.LinkedHashMap<K,V> valueToIndexMap
```
      The mapping of values to their indices.
- Class gov.sandia.cognition.collection.DefaultMultiCollection extends java.util.AbstractCollection<EntryType> implements Serializable
  - Serialized Fields
    - collections
```
java.util.List<E> collections
```
      The set of collections that backs this collection.
- Class gov.sandia.cognition.collection.DoubleArrayList extends gov.sandia.cognition.collection.PrimitiveArrayList implements Serializable
  
  serialVersionUID:
  
  7027037134983162626L
  - Serialized Fields
    - elements
```
double[] elements
```
      The elements array. May be ~50% too large for the current data
- Class gov.sandia.cognition.collection.DynamicArrayMap extends java.util.AbstractMap<java.lang.Integer,ValueType> implements Serializable
  - Serialized Fields
    - array
```
java.lang.Object[] array
```
      The array underneath the mapping. Null values indicate an unassigned key.
    - numValues
```
int numValues
```
      The number of non-null values in the array.
- Class gov.sandia.cognition.collection.FiniteCapacityBuffer extends java.util.AbstractList<DataType> implements Serializable
  - Serialized Fields
    - data
```
java.lang.Object[] data
```
      Underlying data in the buffer
    - head
```
int head
```
      Location of element 0
    - size
```
int size
```
      Number of items in the list
- Class gov.sandia.cognition.collection.IntArrayList extends gov.sandia.cognition.collection.PrimitiveArrayList implements Serializable
  
  serialVersionUID:
  
  -423369949544940448L
  - Serialized Fields
    - elements
```
int[] elements
```
      The elements array. May be ~50% too large for the current data
- Class gov.sandia.cognition.collection.IntegerSpan extends java.util.AbstractSet<java.lang.Integer> implements Serializable
  - Serialized Fields
    - minValue
```
int minValue
```
      Starting index, inclusive
    - maxValue
```
int maxValue
```
      Stopping index, inclusive
- Class gov.sandia.cognition.collection.MultiIterator extends java.lang.Object implements Serializable
  - Serialized Fields
    - currentIterator
```
java.util.Iterator<E> currentIterator
```
      The current iterator.
    - remainingIterators
```
java.util.LinkedList<E> remainingIterators
```
      The iterators themselves.
- Class gov.sandia.cognition.collection.NumberComparator extends AbstractCloneableSerializable implements Serializable
Package gov.sandia.cognition.data.convert
- Class gov.sandia.cognition.data.convert.AbstractDataConverter extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.data.convert.AbstractReverseCachedDataConverter extends AbstractReversibleDataConverter<InputType,OutputType> implements Serializable
- Class gov.sandia.cognition.data.convert.AbstractReversibleDataConverter extends AbstractDataConverter<InputType,OutputType> implements Serializable
- Class gov.sandia.cognition.data.convert.IdentityDataConverter extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.data.convert.ObjectToStringConverter extends AbstractDataConverter<java.lang.Object,java.lang.String> implements Serializable
Package gov.sandia.cognition.data.convert.number
- Class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter extends AbstractReverseCachedDataConverter<java.lang.Boolean,java.lang.Number,DefaultBooleanToNumberConverter.Reverse> implements Serializable
  - Serialized Fields
    - trueValue
```
java.lang.Number trueValue
```
      The number to use to represent a true value.
    - falseValue
```
java.lang.Number falseValue
```
      The number to use to represent a false value.
    - nullValue
```
java.lang.Number nullValue
```
      The number to use to represent a null value.
- Class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter.Reverse extends AbstractReversibleDataConverter<java.lang.Number,java.lang.Boolean> implements Serializable
- Class gov.sandia.cognition.data.convert.number.StringToDoubleConverter extends AbstractReverseCachedDataConverter<java.lang.String,java.lang.Double,ObjectToStringConverter> implements Serializable
- Class gov.sandia.cognition.data.convert.number.StringToIntegerConverter extends AbstractReverseCachedDataConverter<java.lang.String,java.lang.Integer,ObjectToStringConverter> implements Serializable
Package gov.sandia.cognition.data.convert.vector
- Class gov.sandia.cognition.data.convert.vector.AbstractToVectorEncoder extends AbstractDataConverter<InputType,Vector> implements Serializable
  - Serialized Fields
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The vector factory to use to create new vectors.
- Class gov.sandia.cognition.data.convert.vector.NumberConverterToVectorAdapter extends AbstractToVectorEncoder<InputType> implements Serializable
  - Serialized Fields
    - converter
```
DataConverter<InputType,OutputType> converter
```
      The converter to adapt for use with Vectors.
- Class gov.sandia.cognition.data.convert.vector.NumberToVectorEncoder extends AbstractToVectorEncoder<java.lang.Number> implements Serializable
- Class gov.sandia.cognition.data.convert.vector.UniqueBooleanVectorEncoder extends AbstractToVectorEncoder<InputType> implements Serializable
  - Serialized Fields
    - values
```
java.util.List<E> values
```
      The set of possible unique values.
    - booleanConverter
```
DataToVectorEncoder<InputType> booleanConverter
```
      The boolean encoder for the equality comparison between each of the possible values and a given input.
Package gov.sandia.cognition.evaluator
- Class gov.sandia.cognition.evaluator.AbstractStatefulEvaluator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - state
```
CloneableSerializable state
```
      Current state object.
- Class gov.sandia.cognition.evaluator.CompositeEvaluatorList extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - evaluators
```
java.util.ArrayList<E> evaluators
```
      The list of evaluators to compose together.
- Class gov.sandia.cognition.evaluator.CompositeEvaluatorPair extends DefaultPair<Evaluator<? super InputType,? extends IntermediateType>,Evaluator<? super IntermediateType,? extends OutputType>> implements Serializable
- Class gov.sandia.cognition.evaluator.CompositeEvaluatorTriple extends DefaultTriple<Evaluator<? super InputType,? extends FirstIntermediateType>,Evaluator<? super FirstIntermediateType,? extends SecondIntermediateType>,Evaluator<? super SecondIntermediateType,? extends OutputType>> implements Serializable
- Class gov.sandia.cognition.evaluator.ForwardReverseEvaluatorPair extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - forward
```
Evaluator<InputType,OutputType> forward
```
      The forward evaluator from input type to output type.
    - reverse
```
Evaluator<InputType,OutputType> reverse
```
      The reverse evaluator from output type to input type.
- Class gov.sandia.cognition.evaluator.IdentityEvaluator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.evaluator.ValueClamper extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - minimum
```
java.lang.Comparable<T> minimum
```
      The minimum possible value. May be null to not clamp to the minimum.
    - maximum
```
java.lang.Comparable<T> maximum
```
      The maximum possible value. May be null to not clamp to the maximum.
- Class gov.sandia.cognition.evaluator.ValueMapper extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - valueMap
```
java.util.Map<K,V> valueMap
```
      The map to use to map input values to output values.
Package gov.sandia.cognition.factory
- Class gov.sandia.cognition.factory.DefaultFactory extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - createdClass
```
java.lang.Class<T> createdClass
```
      The class whose default constructor is used to create new objects.
- Class gov.sandia.cognition.factory.PrototypeFactory extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - prototype
```
CloneableSerializable prototype
```
      The prototype to create clones from.
Package gov.sandia.cognition.framework
- Class gov.sandia.cognition.framework.AbstractCognitiveModel extends java.lang.Object implements Serializable
- Class gov.sandia.cognition.framework.AbstractCognitiveModelFactory extends java.lang.Object implements Serializable
  - Serialized Fields
    - moduleFactories
```
java.util.ArrayList<E> moduleFactories
```
      The list of CognitiveModuleFactories to use for the model.
- Class gov.sandia.cognition.framework.AbstractSemanticIdentifier extends java.lang.Object implements Serializable
- Class gov.sandia.cognition.framework.CognitiveModelStateChangeEvent extends java.util.EventObject implements Serializable
  - Serialized Fields
    - model
```
CognitiveModel model
```
      The model whose state has changed.
    - state
```
CognitiveModelState state
```
      The new state of the model.
- Class gov.sandia.cognition.framework.DefaultCogxel extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - semanticIdentifier
```
SemanticIdentifier semanticIdentifier
```
      The SemanticIdentifier that identifies the Cogxel.
    - activation
```
double activation
```
      The current activation of the Cogxel.
- Class gov.sandia.cognition.framework.DefaultCogxelFactory extends java.lang.Object implements Serializable
- Class gov.sandia.cognition.framework.DefaultSemanticIdentifier extends AbstractSemanticIdentifier implements Serializable
  - Serialized Fields
    - label
```
SemanticLabel label
```
      The SemanticLabel that is identified.
    - identifier
```
int identifier
```
      The unique identifier for the semantic label.
- Class gov.sandia.cognition.framework.DefaultSemanticIdentifierMap extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - identifierCounter
```
int identifierCounter
```
      The counter of identifiers, which ensures that each one is unique.
    - mapping
```
java.util.LinkedHashMap<K,V> mapping
```
      The mapping of semantic labels to semantic identifiers.
- Class gov.sandia.cognition.framework.DefaultSemanticLabel extends java.lang.Object implements Serializable
  - Serialized Fields
    - label
```
java.lang.String label
```
      The String label.
- Class gov.sandia.cognition.framework.DefaultSemanticNetwork extends java.lang.Object implements Serializable
  - Serialized Fields
    - labelNodeMap
```
java.util.TreeMap<K,V> labelNodeMap
```
      The mapping of labels onto nodes in the network.
- Class gov.sandia.cognition.framework.SemanticIdentifierMapEvent extends java.util.EventObject implements Serializable
  - Serialized Fields
    - map
```
SemanticIdentifierMap map
```
      The map that the event happened in.
    - eventType
```
SemanticIdentifierMapEventType eventType
```
      The type of event that this is.
    - identifier
```
SemanticIdentifier identifier
```
      The SemanticIdentifier causing the event.
Package gov.sandia.cognition.framework.concurrent
- Class gov.sandia.cognition.framework.concurrent.AbstractConcurrentCognitiveModule extends java.lang.Object implements Serializable
- Class gov.sandia.cognition.framework.concurrent.MultithreadedCognitiveModel extends AbstractCognitiveModelLite implements Serializable
  - Serialized Fields
    - modules
```
ConcurrentCognitiveModule[] modules
```
      The CognitiveModules that are part of this model.
    - fixedThreadPool
```
java.util.concurrent.ExecutorService fixedThreadPool
```
      A thread pool for managing concurrent evaluation of modules
- Class gov.sandia.cognition.framework.concurrent.MultithreadedCognitiveModelFactory extends AbstractCognitiveModelFactory implements Serializable
  - Serialized Fields
    - numThreadsInPool
```
int numThreadsInPool
```
      Number of threads to use in the thread pool
Package gov.sandia.cognition.framework.learning
- Class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModule extends AbstractConcurrentCognitiveModule implements Serializable
  - Serialized Fields
    - name
```
java.lang.String name
```
      Name to assign to the module
    - settings
```
EvaluatorBasedCognitiveModuleSettings<InputType,OutputType> settings
```
      The module settings.
    - input
```
java.lang.Object input
```
      A place to temporarily store the input read in by a call to readState; this temporary store is blown away as soon as it used by evaluate, because we NEVER retain state interally across module update cycles
    - output
```
java.lang.Object output
```
      A place to temporarily store the output generated by a call to evaluate; this temporary store is blown away as soon as it used by evaluate, because we NEVER retain state interally across module update cycles
- Class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactory extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - settings
```
EvaluatorBasedCognitiveModuleSettings<InputType,OutputType> settings
```
      The settings for the module.
    - name
```
java.lang.String name
```
      Human-readable name of the module
- Class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleFactoryLearner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - learner
```
BatchLearner<DataType,ResultType> learner
```
      The learner to use to learn the evaluator
    - inputConverter
```
CogxelConverter<DataType> inputConverter
```
      The CogxelConverter used to convert from a CogxelState to InputType
    - outputConverter
```
CogxelConverter<DataType> outputConverter
```
      The CogxelConverter used to convert OutputType to a CogxelState.
    - learningDataConverter
```
CogxelConverter<DataType> learningDataConverter
```
      The CogxelConverter used to convert from a CogxelState to LearningDataType.
    - name
```
java.lang.String name
```
      Human-readable name for this module
- Class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModuleSettings extends java.lang.Object implements Serializable
  - Serialized Fields
    - evaluator
```
Evaluator<InputType,OutputType> evaluator
```
      The evaluator to be used by the module.
    - inputConverter
```
CogxelConverter<DataType> inputConverter
```
      The CogxelConverter used to convert from a CogxelState to InputType.
    - outputConverter
```
CogxelConverter<DataType> outputConverter
```
      The CogxelConverter used to convert OutputType to a CogxelState.
- Class gov.sandia.cognition.framework.learning.StatefulEvaluatorBasedCognitiveModule extends EvaluatorBasedCognitiveModule<InputType,OutputType> implements Serializable
  - Serialized Fields
    - stateWrapper
```
CognitiveModuleStateWrapper stateWrapper
```
      A place to store the wrapper for the CognitiveModuleState that is initialized by readState and later used by writeState
Package gov.sandia.cognition.framework.learning.converter
- Class gov.sandia.cognition.framework.learning.converter.AbstractCogxelConverter extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - semanticIdentifierMap
```
SemanticIdentifierMap semanticIdentifierMap
```
      The SemanticIdentifierMap for the converter.
- Class gov.sandia.cognition.framework.learning.converter.AbstractCogxelPairConverter extends AbstractCogxelConverter<PairType extends Pair<FirstType,SecondType>> implements Serializable
  - Serialized Fields
    - firstConverter
```
CogxelConverter<DataType> firstConverter
```
      The CogxelConverter for the first element of the pair.
    - secondConverter
```
CogxelConverter<DataType> secondConverter
```
      The CogxelConverter for the second element of the pair.
- Class gov.sandia.cognition.framework.learning.converter.CogxelBooleanConverter extends AbstractCogxelConverter<java.lang.Boolean> implements Serializable
  - Serialized Fields
    - label
```
SemanticLabel label
```
      The label of the Cogxel to convert.
    - identifier
```
SemanticIdentifier identifier
```
      The semantic identifier of the Cogxel to convert.
    - cogxelFactory
```
CogxelFactory cogxelFactory
```
      The CogxelFactory to use.
- Class gov.sandia.cognition.framework.learning.converter.CogxelDoubleConverter extends java.lang.Object implements Serializable
  - Serialized Fields
    - label
```
SemanticLabel label
```
      The label of the Cogxel to convert.
    - identifier
```
SemanticIdentifier identifier
```
      The semantic identifier of the Cogxel to convert.
    - semanticIdentifierMap
```
SemanticIdentifierMap semanticIdentifierMap
```
      The SemanticIdentifierMap for the converter.
    - cogxelFactory
```
CogxelFactory cogxelFactory
```
      The CogxelFactory to use.
- Class gov.sandia.cognition.framework.learning.converter.CogxelInputOutputPairConverter extends AbstractCogxelPairConverter<InputType,OutputType,InputOutputPair<InputType,OutputType>> implements Serializable
- Class gov.sandia.cognition.framework.learning.converter.CogxelMatrixConverter extends java.lang.Object implements Serializable
  - Serialized Fields
    - columnConverters
```
java.util.ArrayList<E> columnConverters
```
      Collection CogxelVectorConverters that convert the columns of the matrix
    - semanticIdentifierMap
```
SemanticIdentifierMap semanticIdentifierMap
```
      SemanticIdentifierMap for the converter
- Class gov.sandia.cognition.framework.learning.converter.CogxelTargetEstimatePairConverter extends AbstractCogxelPairConverter<TargetType,EstimateType,TargetEstimatePair<TargetType,EstimateType>> implements Serializable
- Class gov.sandia.cognition.framework.learning.converter.CogxelVectorCollectionConverter extends java.lang.Object implements Serializable
  - Serialized Fields
    - cogxelVectorConverters
```
java.util.Collection<E> cogxelVectorConverters
```
      Collection of CogxelVectorConverters that do the heavy lifting
- Class gov.sandia.cognition.framework.learning.converter.CogxelVectorConverter extends DefaultVectorFactoryContainer implements Serializable
  - Serialized Fields
    - labels
```
java.util.ArrayList<E> labels
```
      The labels for each of the elements in the vector.
    - semanticIdentifierMap
```
SemanticIdentifierMap semanticIdentifierMap
```
      The current SemanticIdentifierMap.
    - identifiers
```
java.util.ArrayList<E> identifiers
```
      The list of SemanticIdentifiers, whose positions correspond to positions in the vector.
    - identifierToIndexMap
```
java.util.HashMap<K,V> identifierToIndexMap
```
      The mapping of SemanticIdentifiers to vector indices.
    - cogxelFactory
```
CogxelFactory cogxelFactory
```
      The CogxelFactory to use.
- Class gov.sandia.cognition.framework.learning.converter.CogxelWeightedInputOutputPairConverter extends java.lang.Object implements Serializable
  - Serialized Fields
    - pairConverter
```
CogxelInputOutputPairConverter<InputType,OutputType> pairConverter
```
      Creates the underlying InputOutputPair
    - weightConverter
```
CogxelConverter<DataType> weightConverter
```
      Adds the weight to the InputOutputPair
Package gov.sandia.cognition.framework.lite
- Class gov.sandia.cognition.framework.lite.AbstractCognitiveModelLite extends AbstractCognitiveModel implements Serializable
  - Serialized Fields
    - numModules
```
int numModules
```
      The number of modules.
    - semanticIdentifierMap
```
DefaultSemanticIdentifierMap semanticIdentifierMap
```
      The semantic identifier database.
    - state
```
CognitiveModelLiteState state
```
      The current state of the model.
- Class gov.sandia.cognition.framework.lite.AbstractSemanticMemoryLite extends java.lang.Object implements Serializable
  - Serialized Fields
    - semanticIdentifierMap
```
SemanticIdentifierMap semanticIdentifierMap
```
      The mapping of semantic labels to semantic identifiers.
    - recognizer
```
PatternRecognizerLite recognizer
```
      The PatternRecognizerLite that is used.
    - outputIdentifiers
```
java.util.ArrayList<E> outputIdentifiers
```
      The mapping of output vector entries to identifiers.
- Class gov.sandia.cognition.framework.lite.ArrayBasedCognitiveModelInput extends java.lang.Object implements Serializable
  - Serialized Fields
    - identifiers
```
SemanticIdentifier[] identifiers
```
      The identifiers to use as inputs.
    - values
```
double[] values
```
      The activation values of the inputs.
- Class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModule extends AbstractConcurrentCognitiveModule implements Serializable
  - Serialized Fields
    - semanticIdentifierMap
```
SemanticIdentifierMap semanticIdentifierMap
```
      The semantic identifier map. Currently unused, but provided because there may be a need to support SemanticLabels instead of identifiers later on.
    - cogxelFactory
```
CogxelFactory cogxelFactory
```
      The factory for creating Cogxels for perception.
    - input
```
ArrayBasedCognitiveModelInput input
```
      A place to temporarily store the input read in by a call to readState; this temporary store is blown away as soon as it used by writeState, because we NEVER retain state interally across module update cycles
- Class gov.sandia.cognition.framework.lite.ArrayBasedPerceptionModuleFactory extends java.lang.Object implements Serializable
  - Serialized Fields
    - cogxelFactory
```
CogxelFactory cogxelFactory
```
      The CogxelFactory for the module to use in creating Cogxels.
- Class gov.sandia.cognition.framework.lite.BooleanActivatableCogxel extends DefaultCogxel implements Serializable
  - Serialized Fields
    - activated
```
boolean activated
```
      A boolean indicating whether the cogxel is activated.
- Class gov.sandia.cognition.framework.lite.BooleanActivatableCogxelFactory extends java.lang.Object implements Serializable
- Class gov.sandia.cognition.framework.lite.CognitiveModelLite extends AbstractCognitiveModelLite implements Serializable
  - Serialized Fields
    - modules
```
CognitiveModule[] modules
```
      The CognitiveModules that are part of this model.
- Class gov.sandia.cognition.framework.lite.CognitiveModelLiteFactory extends AbstractCognitiveModelFactory implements Serializable
- Class gov.sandia.cognition.framework.lite.CognitiveModelLiteState extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - initialized
```
boolean initialized
```
      A flag indicating if the state has been initialized or not.
    - input
```
CognitiveModelInput input
```
      The input to the model.
    - cogxels
```
CogxelStateLite cogxels
```
      The state of the Cogxels.
    - moduleStatesArray
```
CognitiveModuleState[] moduleStatesArray
```
      The states of the modules.
- Class gov.sandia.cognition.framework.lite.CognitiveModuleStateWrapper extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - internalState
```
CloneableSerializable internalState
```
      The internal state object that is wrapped.
- Class gov.sandia.cognition.framework.lite.CogxelStateLite extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - cogxels
```
DynamicArrayMap<ValueType> cogxels
```
      The underlying mapping of identifiers to cogxels.
- Class gov.sandia.cognition.framework.lite.MutableSemanticMemoryLite extends AbstractSemanticMemoryLite implements Serializable
  - Serialized Fields
    - mutableRecognizer
```
MutablePatternRecognizerLite mutableRecognizer
```
      The mutable pattern recognizer to modify.
    - identifierToInputIndexMap
```
java.util.HashMap<K,V> identifierToInputIndexMap
```
      The mapping of identifier number to input vector index number.
    - nodeSet
```
java.util.HashSet<E> nodeSet
```
      The set of nodes used by the memory.
- Class gov.sandia.cognition.framework.lite.MutableSemanticMemoryLiteFactory extends java.lang.Object implements Serializable
  - Serialized Fields
    - recognizer
```
MutablePatternRecognizerLite recognizer
```
      The module settings.
- Class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLite extends AbstractSemanticMemoryLite implements Serializable
  - Serialized Fields
    - sharedSettings
```
SharedSemanticMemoryLiteSettings sharedSettings
```
      The shared settings for this semantic memory.
    - minIdentifier
```
int minIdentifier
```
      The minimum identifier number.
    - maxIdentifier
```
int maxIdentifier
```
      The maximum identifier number.
    - identifierToInputIndexMap
```
int[] identifierToInputIndexMap
```
      The mapping of input indentifier to input index.
- Class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLiteFactory extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - settings
```
SharedSemanticMemoryLiteSettings settings
```
      The shared settings between the modules.
- Class gov.sandia.cognition.framework.lite.SharedSemanticMemoryLiteSettings extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - recognizer
```
PatternRecognizerLite recognizer
```
      The recognizer to use in the memory.
- Class gov.sandia.cognition.framework.lite.SimplePatternRecognizer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - nodes
```
java.util.ArrayList<E> nodes
```
      The nodes in the recognition network, sorted by how they are to appear in the vector.
    - nodeToIDMap
```
java.util.HashMap<K,V> nodeToIDMap
```
      The mapping of semantic labels to their index in the vector.
    - matrix
```
Matrix matrix
```
      The matrix underlying the pattern recognizer.
    - nodesChangedSinceLastUpdate
```
boolean nodesChangedSinceLastUpdate
```
      True if the set of nodes has changed since the last update.
- Class gov.sandia.cognition.framework.lite.SimplePatternRecognizerState extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - labels
```
java.util.ArrayList<E> labels
```
      The array of semantic labels that the state vector has. This is stored as a private copy in the state object because the module can have labels added or removed. If that happens then the module will need to update the state based on the new labels.
    - stateVector
```
Vector stateVector
```
      The state vector.
- Class gov.sandia.cognition.framework.lite.VectorBasedCognitiveModelInput extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - identifiers
```
SemanticIdentifier[] identifiers
```
      Identifiers to use associate with the inputs
    - values
```
Vector values
```
      Activation values of the inputs
- Class gov.sandia.cognition.framework.lite.VectorBasedPerceptionModule extends java.lang.Object implements Serializable
  - Serialized Fields
    - cogxelFactory
```
CogxelFactory cogxelFactory
```
      Factory for creating Cogxels for perception
- Class gov.sandia.cognition.framework.lite.VectorBasedPerceptionModuleFactory extends java.lang.Object implements Serializable
  - Serialized Fields
    - cogxelFactory
```
CogxelFactory cogxelFactory
```
      CogxelFactory for the module to use in creating Cogxels
Package gov.sandia.cognition.graph
- Class gov.sandia.cognition.graph.DenseMemoryGraph extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  52275907258580715L
  - Serialized Fields
    - nodes
```
DefaultIndexer<ValueType> nodes
```
      Node objects are stored herein. Their "id" is their position in the array. This allows O(1) lookup of the node given the id. Storage: O(n).
    - edges
```
IntArrayList edges
```
      This links source node and destination node for all edges. Each pair of node id values are in order. The edge is identified by the half the index into this array (because this stores them two-in-a-row). Storage: O(m).
    - isOptimized
```
boolean isOptimized
```
      Stores whether the edge list is sorted. Set to false after each addEdge. Set to true after optimizeEdges is called. Storage: O(1).
- Class gov.sandia.cognition.graph.WeightedDenseMemoryGraph extends DenseMemoryGraph<NodeNameType> implements Serializable
  
  serialVersionUID:
  
  9009145019650654200L
  - Serialized Fields
    - weights
```
DoubleArrayList weights
```
      Storage for the weights -- This stays in-line with the edges when the edges are added and sorted
Package gov.sandia.cognition.hash
- Class gov.sandia.cognition.hash.AbstractHashFunction extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.hash.Eva32Hash extends AbstractHashFunction implements Serializable
- Class gov.sandia.cognition.hash.Eva64Hash extends AbstractHashFunction implements Serializable
- Class gov.sandia.cognition.hash.FNV1a32Hash extends AbstractHashFunction implements Serializable
- Class gov.sandia.cognition.hash.FNV1a64Hash extends AbstractHashFunction implements Serializable
- Class gov.sandia.cognition.hash.MD5Hash extends AbstractHashFunction implements Serializable
  - Serialized Fields
    - buf
```
int[] buf
```
      These were originally unsigned ints. This Java code makes an effort to avoid sign traps. buf[] is where the hash accumulates.
    - bits
```
long bits
```
      This is the count of bits hashed so far.
    - in
```
byte[] in
```
      This is a buffer where we stash bytes until we have enough (64) to perform a transform operation.
- Class gov.sandia.cognition.hash.Murmur32Hash extends AbstractHashFunction implements Serializable
- Class gov.sandia.cognition.hash.Prime32Hash extends AbstractHashFunction implements Serializable
- Class gov.sandia.cognition.hash.Prime64Hash extends AbstractHashFunction implements Serializable
- Class gov.sandia.cognition.hash.SHA1Hash extends AbstractHashFunction implements Serializable
- Class gov.sandia.cognition.hash.SHA256Hash extends AbstractHashFunction implements Serializable
- Class gov.sandia.cognition.hash.SHA512Hash extends AbstractHashFunction implements Serializable
Package gov.sandia.cognition.io
- Class gov.sandia.cognition.io.CSVParseException extends java.lang.Exception implements Serializable
Package gov.sandia.cognition.io.serialization
- Class gov.sandia.cognition.io.serialization.AbstractFileSerializationHandler extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.io.serialization.AbstractStreamSerializationHandler extends AbstractFileSerializationHandler<SerializedType> implements Serializable
- Class gov.sandia.cognition.io.serialization.AbstractTextSerializationHandler extends AbstractStreamSerializationHandler<SerializedType> implements Serializable
  - Serialization Methods
    - readObject
```
public java.lang.Object readObject(java.io.InputStream stream)
                            throws java.io.IOException,
                                   java.lang.ClassNotFoundException
```
      Throws:
      
      java.io.IOException - If there is an i/o error.
      
      java.lang.ClassNotFoundException - If a class cannot be found.
    - writeObject
```
public void writeObject(java.io.OutputStream stream,
                        SerializedType object)
                 throws java.io.IOException
```
      Throws:
      
      java.io.IOException - If there is an i/o error.
- Class gov.sandia.cognition.io.serialization.GZIPSerializationHandler extends AbstractStreamSerializationHandler<SerializedType> implements Serializable
  - Serialization Methods
    - readObject
```
public java.lang.Object readObject(java.io.InputStream stream)
                            throws java.io.IOException,
                                   java.lang.ClassNotFoundException
```
      Throws:
      
      java.io.IOException - If there is an i/o error.
      
      java.lang.ClassNotFoundException - If a class cannot be found.
    - writeObject
```
public void writeObject(java.io.OutputStream stream,
                        SerializedType object)
                 throws java.io.IOException
```
      Throws:
      
      java.io.IOException - If there is an i/o error.
  - Serialized Fields
    - baseHandler
```
StreamSerializationHandler<SerializedType> baseHandler
```
      The base handler that is being wrapped in a GZip.
- Class gov.sandia.cognition.io.serialization.JavaDefaultBinarySerializationHandler extends AbstractStreamSerializationHandler<java.io.Serializable> implements Serializable
  - Serialization Methods
    - readObject
```
public java.lang.Object readObject(java.io.InputStream stream)
                            throws java.io.IOException,
                                   java.lang.ClassNotFoundException
```
      Throws:
      
      java.io.IOException - If there is an i/o error.
      
      java.lang.ClassNotFoundException - If a class cannot be found.
    - writeObject
```
public void writeObject(java.io.OutputStream stream,
                        java.io.Serializable object)
                 throws java.io.IOException
```
      Throws:
      
      java.io.IOException - If there is an i/o error.
- Class gov.sandia.cognition.io.serialization.XStreamSerializationHandler extends AbstractTextSerializationHandler<java.io.Serializable> implements Serializable
  - Serialization Methods
    - readObject
```
public java.lang.Object readObject(java.io.Reader reader)
                            throws java.io.IOException
```
      Throws:
      
      java.io.IOException - If there is an i/o error.
    - writeObject
```
public void writeObject(java.io.Writer writer,
                        java.io.Serializable object)
                 throws java.io.IOException
```
      Throws:
      
      java.io.IOException - If there is an i/o error.
Package gov.sandia.cognition.learning.algorithm
- Class gov.sandia.cognition.learning.algorithm.AbstractAnytimeBatchLearner extends AbstractAnytimeAlgorithm<ResultType> implements Serializable
  - Serialized Fields
    - keepGoing
```
boolean keepGoing
```
      Indicates whether or not the learner should make another step.
    - data
```
java.lang.Object data
```
      The data to learn from.
- Class gov.sandia.cognition.learning.algorithm.AbstractAnytimeSupervisedBatchLearner extends AbstractAnytimeBatchLearner<java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>>,ResultType extends Evaluator<? super InputType,? extends OutputType>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.AbstractBatchLearnerContainer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - learner
```
BatchLearner<DataType,ResultType> learner
```
      The wrapped learner.
- Class gov.sandia.cognition.learning.algorithm.AbstractSupervisedBatchAndIncrementalLearner extends AbstractBatchAndIncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType extends Evaluator<? super InputType,? extends OutputType>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.CompositeBatchLearnerPair extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - firstLearner
```
BatchLearner<DataType,ResultType> firstLearner
```
      The first learner that is trained on the input data.
    - secondLearner
```
BatchLearner<DataType,ResultType> secondLearner
```
      The second learner that is trained on the output of the evaluator created by the first learner.
- Class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner extends AbstractBatchLearnerContainer<BatchLearner<? super java.util.Collection<? extends InputOutputPair<? extends TransformedInputType,TransformedOutputType>>,? extends Evaluator<? super TransformedInputType,? extends TransformedOutputType>>> implements Serializable
  - Serialized Fields
    - inputLearner
```
BatchLearner<DataType,ResultType> inputLearner
```
      The unsupervised learning algorithm for creating the input transformation.
    - outputLearner
```
BatchLearner<DataType,ResultType> outputLearner
```
      The unsupervised learning algorithm for creating the output transformation, which must be reversible for evaluation.
- Class gov.sandia.cognition.learning.algorithm.SequencePredictionLearner extends AbstractBatchLearnerContainer<BatchLearner<? super java.util.Collection<? extends InputOutputPair<? extends DataType,DataType>>,? extends LearnedType>> implements Serializable
  - Serialized Fields
    - predictionHorizon
```
int predictionHorizon
```
      The prediction horizon, which is the number of samples in the future to try to learn to predict. It must be a positive number.
- Class gov.sandia.cognition.learning.algorithm.TimeSeriesPredictionLearner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - predictionHorizon
```
int predictionHorizon
```
      Number of samples into the future to predict.
    - supervisedLearner
```
SupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> supervisedLearner
```
      Learning algorithm that does the heavy lifting.
Package gov.sandia.cognition.learning.algorithm.annealing
- Class gov.sandia.cognition.learning.algorithm.annealing.SimulatedAnnealer extends AbstractAnytimeBatchLearner<CostParametersType,AnnealedType> implements Serializable
  - Serialized Fields
    - cost
```
CostFunction<EvaluatedType,CostParametersType> cost
```
      The cost function to minimize.
    - perturber
```
Perturber<PerturbedType> perturber
```
      The perturbing function to use to perturb the objects.
    - temperature
```
double temperature
```
      The current temperature.
    - maxIterationsWithoutImprovement
```
int maxIterationsWithoutImprovement
```
      The maximum number of iterations to go without improvement before stopping.
    - iterationsWithoutImprovement
```
int iterationsWithoutImprovement
```
      The number of iterations since the last improvement.
    - coolingFactor
```
double coolingFactor
```
      The cooling factor applied at each step.
    - random
```
java.util.Random random
```
      The random number generator to use.
    - bestSoFar
```
java.lang.Object bestSoFar
```
      The best state found so far.
    - bestSoFarScore
```
double bestSoFarScore
```
      The score for the best state found so far.
    - current
```
java.lang.Object current
```
      The current state.
    - currentScore
```
double currentScore
```
      The score of the current state.
- Class gov.sandia.cognition.learning.algorithm.annealing.VectorizablePerturber extends AbstractRandomized implements Serializable
  - Serialized Fields
    - covarianceSqrt
```
Matrix covarianceSqrt
```
      The covariance square root matrix to use while perturbing.
Package gov.sandia.cognition.learning.algorithm.baseline
- Class gov.sandia.cognition.learning.algorithm.baseline.ConstantLearner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - value
```
java.lang.Object value
```
      The result of learning.
- Class gov.sandia.cognition.learning.algorithm.baseline.IdentityLearner extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.baseline.MeanLearner extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.baseline.MostFrequentLearner extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.baseline.WeightedMeanLearner extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.baseline.WeightedMostFrequentLearner extends AbstractCloneableSerializable implements Serializable
Package gov.sandia.cognition.learning.algorithm.bayes
- Class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - conditionalProbabilities
```
java.util.Map<K,V> conditionalProbabilities
```
      Class conditional probability table.
    - priorProbabilities
```
DefaultDataDistribution<KeyType> priorProbabilities
```
      Table of category priors.
    - inputDimensionality
```
int inputDimensionality
```
      Assumed dimensionality of the inputs.
- Class gov.sandia.cognition.learning.algorithm.bayes.DiscreteNaiveBayesCategorizer.Learner extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - priors
```
DataDistribution<DataType> priors
```
      The prior distribution for the categorizer.
    - conditionals
```
java.util.Map<K,V> conditionals
```
      The mapping of category to the conditional distribution for the category with one probability density function for each dimension.
- Class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.BatchGaussianLearner extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.Learner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - distributionEstimator
```
DistributionEstimator<ObservationType,DistributionType extends Distribution<? extends ObservationType>> distributionEstimator
```
      The distributionLearner for the distribution of each dimension of each category.
- Class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.OnlineLearner extends AbstractBatchAndIncrementalLearner<InputOutputPair<? extends Vectorizable,CategoryType>,VectorNaiveBayesCategorizer<CategoryType,DistributionType extends UnivariateProbabilityDensityFunction>> implements Serializable
  - Serialized Fields
    - distributionLearner
```
IncrementalLearner<DataType,ResultType> distributionLearner
```
      The incremental learner for the distribution used to represent each dimension. By the generic, it must learn a univariate probability density function.
Package gov.sandia.cognition.learning.algorithm.clustering
- Class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation extends AbstractAnytimeBatchLearner<java.util.Collection<? extends DataType>,java.util.Collection<CentroidCluster<DataType>>> implements Serializable
  - Serialized Fields
    - divergence
```
DivergenceFunction<FirstType,SecondType> divergence
```
      The divergence function to use.
    - selfDivergence
```
double selfDivergence
```
      The value to use for self-divergence. Controls the number of clusters created.
    - dampingFactor
```
double dampingFactor
```
      The damping factor (lambda). It must be between 0.0 and 1.0.
    - oneMinusDampingFactor
```
double oneMinusDampingFactor
```
      The cached value of one minus the damping factor.
    - examples
```
java.util.ArrayList<E> examples
```
      The examples.
    - similarities
```
double[][] similarities
```
      The array of example-example similarities.
    - responsibilities
```
double[][] responsibilities
```
      The array of example-example responsibilities.
    - availabilities
```
double[][] availabilities
```
      The array of example-example availabilities.
    - assignments
```
int[] assignments
```
      The assignments of each example to an exemplar (cluster).
    - changedCount
```
int changedCount
```
      The number of examples that have changed assignments in the last iteration.
    - clusters
```
java.util.HashMap<K,V> clusters
```
      The clusters that have been found so far. It is a sparse mapping since we expect there to be few clusters.
- Class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer extends AbstractAnytimeBatchLearner<java.util.Collection<? extends DataType>,java.util.Collection<ClusterType extends Cluster<DataType>>> implements Serializable
  - Serialized Fields
    - divergenceFunction
```
ClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> divergenceFunction
```
      The divergence function used to find the distance between two clusters.
    - creator
```
ClusterCreator<ClusterType extends Cluster<DataType>,DataType> creator
```
      The merger used to merge two clusters into one element.
    - minNumClusters
```
int minNumClusters
```
      The minimum number of clusters allowed.
    - maxDistance
```
double maxDistance
```
      The maximum distance between clusters allowed.
    - clusters
```
java.util.ArrayList<E> clusters
```
      The current set of clusters.
    - clustersHierarchy
```
java.util.ArrayList<E> clustersHierarchy
```
      The current set of hierarchical clusters.
- Class gov.sandia.cognition.learning.algorithm.clustering.AgglomerativeClusterer.HierarchyNode extends BinaryClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> implements Serializable
  - Serialized Fields
    - childrenDivergence
```
double childrenDivergence
```
      The divergence between the two children, if they exist.
- Class gov.sandia.cognition.learning.algorithm.clustering.DBSCANClusterer extends AbstractAnytimeBatchLearner<java.util.Collection<? extends DataType extends Vectorizable>,java.util.Collection<ClusterType extends Cluster<DataType>>> implements Serializable
  - Serialized Fields
    - eps
```
double eps
```
      The radius of a neighborhood.
    - minSamples
```
int minSamples
```
      The minimum number of samples in the neighborhood for the point to be considered a core point.
    - metric
```
Semimetric<InputType> metric
```
      The distance metric to use.
    - spatialIndex
```
KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> spatialIndex
```
      A spatial index of the points to improve neighborhood querying.
    - clusterCount
```
int clusterCount
```
      Number of clusters created so far.
    - clustered
```
java.util.HashSet<E> clustered
```
      Set of points that have been clustered so far.
    - visited
```
java.util.HashSet<E> visited
```
      Set of points that have been visited so far.
    - points
```
java.util.ArrayList<E> points
```
      All the data in an indexible structure.
    - creator
```
ClusterCreator<ClusterType extends Cluster<DataType>,DataType> creator
```
      The cluster creator for creating clusters.
    - clusters
```
java.util.ArrayList<E> clusters
```
      The current set of clusters.
    - currentCluster
```
java.util.ArrayList<E> currentCluster
```
      The current cluster.
    - noiseCluster
```
java.util.ArrayList<E> noiseCluster
```
      The cluster for points marked as noise.
    - pointIndex
```
int pointIndex
```
      Index of the next point to process in step().
- Class gov.sandia.cognition.learning.algorithm.clustering.DirichletProcessClustering extends AnytimeAlgorithmWrapper<java.util.Collection<GaussianCluster>,DirichletProcessMixtureModel<Vector>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer extends AbstractAnytimeBatchLearner<java.util.Collection<? extends DataType>,java.util.Collection<ClusterType extends Cluster<DataType>>> implements Serializable
  - Serialized Fields
    - numRequestedClusters
```
int numRequestedClusters
```
      The number of clusters requested.
    - initializer
```
FixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType> initializer
```
      The initializer for the algorithm.
    - divergenceFunction
```
ClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> divergenceFunction
```
      The divergence function between cluster being used.
    - creator
```
ClusterCreator<ClusterType extends Cluster<DataType>,DataType> creator
```
      The cluster creator for creating clusters.
    - clusters
```
java.util.ArrayList<E> clusters
```
      The current set of clusters.
    - assignments
```
int[] assignments
```
      The current assignments of elements to clusters.
    - clusterCounts
```
int[] clusterCounts
```
      The current number of elements assigned to each cluster.
    - numChanged
```
int numChanged
```
      Returns the number of samples that changed assignment between iterations
- Class gov.sandia.cognition.learning.algorithm.clustering.KMeansClustererWithRemoval extends KMeansClusterer<DataType,ClusterType extends Cluster<DataType>> implements Serializable
  - Serialized Fields
    - removalThreshold
```
double removalThreshold
```
      fraction of the expected number of data points assigned to a cluster below which the cluster will be removed. (Suppose there are 1000 datapoint, 10 clusters, and removalThreshold=0.1. A cluster may be removed only if is has membership less than 0.1*1000/10= 10 elements assigned to it.)
- Class gov.sandia.cognition.learning.algorithm.clustering.KMeansFactory extends AbstractRandomized implements Serializable
  - Serialized Fields
    - numClusters
```
int numClusters
```
      Number of clusters to use. Must be positive.
- Class gov.sandia.cognition.learning.algorithm.clustering.MiniBatchKMeansClusterer extends KMeansClusterer<Vector,MiniBatchCentroidCluster> implements Serializable
  
  serialVersionUID:
  
  2587013040037999607L
  - Serialized Fields
    - random
```
java.util.Random random
```
      The random number generator to use for initialization and subset selection.
    - minibatchSize
```
int minibatchSize
```
      The size of the mini-batches.
    - dataIndices
```
java.util.List<E> dataIndices
```
      Indices of the data. This should be a range of ints= [0, data.size)
    - stoppingCriterion
```
double stoppingCriterion
```
      Indicates if the iteration process should stop early. If the fraction of samples that changed assignment is lower than this number, iteration stops.
- Class gov.sandia.cognition.learning.algorithm.clustering.OptimizedKMeansClusterer extends KMeansClusterer<DataType,CentroidCluster<DataType>> implements Serializable
  - Serialized Fields
    - metric
```
Metric<EvaluatedType> metric
```
      The metric being used.
    - lowerBounds
```
double[][] lowerBounds
```
      The lower bounds on the distances to the clusters.
    - upperBounds
```
double[] upperBounds
```
      The upper bounds on the distance to the current assigned cluster.
    - clusterDistances
```
double[][] clusterDistances
```
      The distances between clusters.
- Class gov.sandia.cognition.learning.algorithm.clustering.ParallelizedKMeansClusterer extends KMeansClusterer<DataType,ClusterType extends Cluster<DataType>> implements Serializable
  - Serialized Fields
    - assignmentTasks
```
java.util.ArrayList<E> assignmentTasks
```
      Parallel tasks that assign the data points to clusters
    - clusterCreatorTask
```
java.util.ArrayList<E> clusterCreatorTask
```
      Parallel tasks that creates clusters from the assigned data points
    - assignmentList
```
java.util.Collection<E> assignmentList
```
      ArrayList of assignments from the subtasks
    - newAssignments
```
int[] newAssignments
```
      Array of new assignments
- Class gov.sandia.cognition.learning.algorithm.clustering.PartitionalClusterer extends AbstractAnytimeBatchLearner<java.util.Collection<? extends DataType>,java.util.Collection<ClusterType extends Cluster<DataType>>> implements Serializable
  - Serialized Fields
    - clusterDivergenceFunction
```
WithinClusterDivergence<ClusterType extends Cluster<DataType>,DataType> clusterDivergenceFunction
```
      The divergence function used to find the distance between two clusters.
    - divergenceFunction
```
DivergenceFunction<FirstType,SecondType> divergenceFunction
```
      An optional DivergenceFunction that is used to create a WithinClusterDivergence function via a WithinClusterDivergenceWrapper.
    - tolerance
```
double tolerance
```
      Tolerance for determining when improvement has been made. The default value is .
    - creator
```
IncrementalClusterCreator<ClusterType extends Cluster<DataType>,DataType> creator
```
      The merger used to merge two clusters into one cluster.
    - minClusterSize
```
int minClusterSize
```
      The minimum number of elements per cluster allowed.
    - maxCriterionDecrease
```
double maxCriterionDecrease
```
      The maximum decrease in training criterion allowed.
    - clusterIndex
```
int clusterIndex
```
      The index of the next cluster to split.
    - random
```
java.util.Random random
```
      The source of randomness used during initial partitioning.
    - numRequestedClusters
```
int numRequestedClusters
```
      The number of clusters requested.
    - useCachedClusters
```
boolean useCachedClusters
```
      Whether or not the current learning is using cached cluster results.
Package gov.sandia.cognition.learning.algorithm.clustering.cluster
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.CentroidCluster extends DefaultCluster<ClusterType> implements Serializable
  - Serialized Fields
    - centroid
```
java.lang.Object centroid
```
      The center of the cluster.
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultCluster extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - index
```
int index
```
      The index of the cluster in the collection of clusters.
    - members
```
java.util.ArrayList<E> members
```
      The members of the cluster.
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultClusterCreator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.DefaultIncrementalClusterCreator extends DefaultClusterCreator<DataType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.GaussianCluster extends DefaultCluster<Vector> implements Serializable
  - Serialized Fields
    - gaussian
```
MultivariateGaussian.PDF gaussian
```
      The Gaussian distribution that the cluster represents.
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.GaussianClusterCreator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - defaultCovariance
```
double defaultCovariance
```
      amount to add to the diagonals of the covariance matrix, typically on the order of 1e-4.
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.MedoidClusterCreator extends DefaultDivergenceFunctionContainer<DataType,DataType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.MiniBatchCentroidCluster extends CentroidCluster<Vector> implements Serializable
  - Serialized Fields
    - numUpdates
```
int numUpdates
```
      The number of data points that have been used to calculate this centroid.
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.NormalizedCentroidCluster extends CentroidCluster<ClusterType> implements Serializable
  - Serialized Fields
    - normalizedCentroid
```
java.lang.Object normalizedCentroid
```
      The normalized center of the cluster.
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.NormalizedCentroidClusterCreator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.VectorMeanCentroidClusterCreator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.cluster.VectorMeanMiniBatchCentroidClusterCreator extends AbstractCloneableSerializable implements Serializable
  
  serialVersionUID:
  
  1512395430699067693L
Package gov.sandia.cognition.learning.algorithm.clustering.divergence
- Class gov.sandia.cognition.learning.algorithm.clustering.divergence.AbstractClusterToClusterDivergenceFunction extends DefaultDivergenceFunctionContainer<DataType,DataType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.divergence.CentroidClusterDivergenceFunction extends DefaultDivergenceFunctionContainer<DataType,DataType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterCentroidDivergenceFunction extends AbstractClusterToClusterDivergenceFunction<CentroidCluster<DataType>,DataType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterCompleteLinkDivergenceFunction extends AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterMeanLinkDivergenceFunction extends AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterSingleLinkDivergenceFunction extends AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.divergence.GaussianClusterDivergenceFunction extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.divergence.WithinClusterDivergenceWrapper extends java.lang.Object implements Serializable
  - Serialized Fields
    - divergenceFunction
```
DivergenceFunction<FirstType,SecondType> divergenceFunction
```
      The divergence function.
- Class gov.sandia.cognition.learning.algorithm.clustering.divergence.WithinNormalizedCentroidClusterCosineDivergence extends java.lang.Object implements Serializable
Package gov.sandia.cognition.learning.algorithm.clustering.hierarchy
- Class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.AbstractClusterHierarchyNode extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - cluster
```
Cluster<ClusterType> cluster
```
      The cluster associated with the node.
- Class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.BinaryClusterHierarchyNode extends AbstractClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> implements Serializable
  - Serialized Fields
    - firstChild
```
ClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> firstChild
```
      The first child node.
    - secondChild
```
ClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> secondChild
```
      The second child node.
- Class gov.sandia.cognition.learning.algorithm.clustering.hierarchy.DefaultClusterHierarchyNode extends AbstractClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> implements Serializable
  - Serialized Fields
    - children
```
java.util.List<E> children
```
      The list of children.
Package gov.sandia.cognition.learning.algorithm.clustering.initializer
- Class gov.sandia.cognition.learning.algorithm.clustering.initializer.AbstractMinDistanceFixedClusterInitializer extends DefaultDivergenceFunctionContainer<DataType,DataType> implements Serializable
  - Serialized Fields
    - creator
```
ClusterCreator<ClusterType extends Cluster<DataType>,DataType> creator
```
      The ClusterCreator to create the initial clusters from.
    - random
```
java.util.Random random
```
      The random number generator to use.
- Class gov.sandia.cognition.learning.algorithm.clustering.initializer.DistanceSamplingClusterInitializer extends AbstractMinDistanceFixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.initializer.GreedyClusterInitializer extends AbstractMinDistanceFixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.clustering.initializer.NeighborhoodGaussianClusterInitializer extends AbstractRandomized implements Serializable
  - Serialized Fields
    - defaultCovariance
```
double defaultCovariance
```
      default diagonal covariance scaling factor
    - randomRange
```
double randomRange
```
      range of the neighborhood from which to place the cluster
- Class gov.sandia.cognition.learning.algorithm.clustering.initializer.RandomClusterInitializer extends AbstractRandomized implements Serializable
  - Serialized Fields
    - creator
```
ClusterCreator<ClusterType extends Cluster<DataType>,DataType> creator
```
      The creator for new clusters.
Package gov.sandia.cognition.learning.algorithm.confidence
- Class gov.sandia.cognition.learning.algorithm.confidence.AdaptiveRegularizationOfWeights extends AbstractSupervisedBatchAndIncrementalLearner<Vectorizable,java.lang.Boolean,DefaultConfidenceWeightedBinaryCategorizer> implements Serializable
  - Serialized Fields
    - r
```
double r
```
      The r parameter that controls regularization weight. Must be positive.
- Class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviation extends AbstractSupervisedBatchAndIncrementalLearner<Vectorizable,java.lang.Boolean,DiagonalConfidenceWeightedBinaryCategorizer> implements Serializable
  - Serialized Fields
    - confidence
```
double confidence
```
      The confidence to use for updating. Must be in [0.5, 1]. Called eta in the paper.
    - defaultVariance
```
double defaultVariance
```
      The default variance, which the diagonal of the covariance matrix is initialized to. Must be positive. Called a in the paper.
    - phi
```
double phi
```
      Phi is the standard score computed from the confidence.
    - psi
```
double psi
```
      Psi is the cached value 1 + phi^2 / 2.
    - epsilon
```
double epsilon
```
      Epsilon is the cached value 1 + phi^2.
- Class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalDeviationProject extends ConfidenceWeightedDiagonalDeviation implements Serializable
- Class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVariance extends AbstractSupervisedBatchAndIncrementalLearner<Vectorizable,java.lang.Boolean,DiagonalConfidenceWeightedBinaryCategorizer> implements Serializable
  - Serialized Fields
    - confidence
```
double confidence
```
      The confidence to use for updating. Must be in [0, 1]. Called eta in the paper.
    - defaultVariance
```
double defaultVariance
```
      The default variance, which the diagonal of the covariance matrix is initialized to. Must be positive. Called a in the paper.
    - phi
```
double phi
```
      Phi is the standard score computed from the confidence.
- Class gov.sandia.cognition.learning.algorithm.confidence.ConfidenceWeightedDiagonalVarianceProject extends ConfidenceWeightedDiagonalVariance implements Serializable
Package gov.sandia.cognition.learning.algorithm.delta
- Class gov.sandia.cognition.learning.algorithm.delta.AbstractDeltaCategorizer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - learner
```
AbstractDeltaCategorizer.AbstractLearner<CategoryType> learner
```
      The learner that was used to train this categorizer.
    - featureStddev
```
java.util.ArrayList<E> featureStddev
```
      The stddev of each feature.
- Class gov.sandia.cognition.learning.algorithm.delta.AbstractDeltaCategorizer.AbstractLearner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - trainingSet
```
java.util.Collection<E> trainingSet
```
      The training set.
- Class gov.sandia.cognition.learning.algorithm.delta.BurrowsDeltaCategorizer extends AbstractDeltaCategorizer<CategoryType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.delta.BurrowsDeltaCategorizer.Learner extends AbstractDeltaCategorizer.AbstractLearner<CategoryType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.delta.CosineDeltaCategorizer extends AbstractDeltaCategorizer<CategoryType> implements Serializable
  - Serialized Fields
    - featureMeans
```
java.util.ArrayList<E> featureMeans
```
      For Cosine Delta we also need to keep track of the overall mean of the occurrences of each feature.
- Class gov.sandia.cognition.learning.algorithm.delta.CosineDeltaCategorizer.Learner extends AbstractDeltaCategorizer.AbstractLearner<CategoryType> implements Serializable
Package gov.sandia.cognition.learning.algorithm.ensemble
- Class gov.sandia.cognition.learning.algorithm.ensemble.AbstractBaggingLearner extends AbstractAnytimeSupervisedBatchLearner<InputType,OutputType,EnsembleType extends Evaluator<? super InputType,? extends OutputType>> implements Serializable
  - Serialized Fields
    - learner
```
BatchLearner<DataType,ResultType> learner
```
      The learner to use to create the categorizer for each iteration.
    - percentToSample
```
double percentToSample
```
      The percentage of the data to sample with replacement on each iteration. Must be positive. Represented as a floating point number with 1.0 meaning 100%.
    - random
```
java.util.Random random
```
      The random number generator to use.
- Class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria extends AbstractIterativeAlgorithmListener implements Serializable
  - Serialized Fields
    - smoothingWindowSize
```
int smoothingWindowSize
```
      The size of window of data to look at to determine if learning has hit a minimum.
- Class gov.sandia.cognition.learning.algorithm.ensemble.AbstractUnweightedEnsemble extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - members
```
java.util.List<E> members
```
      The members of the ensemble.
- Class gov.sandia.cognition.learning.algorithm.ensemble.AbstractWeightedEnsemble extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - members
```
java.util.List<E> members
```
      The members of the ensemble.
- Class gov.sandia.cognition.learning.algorithm.ensemble.AdaBoost extends AbstractAnytimeSupervisedBatchLearner<InputType,java.lang.Boolean,WeightedBinaryEnsemble<InputType,Evaluator<? super InputType,? extends java.lang.Boolean>>> implements Serializable
  - Serialized Fields
    - weakLearner
```
BatchLearner<DataType,ResultType> weakLearner
```
      The "weak learner" that must learn from the weighted input-output pairs on each iteration.
- Class gov.sandia.cognition.learning.algorithm.ensemble.AdditiveEnsemble extends AbstractUnweightedEnsemble<MemberType extends Evaluator<? super InputType,? extends java.lang.Number>> implements Serializable
  - Serialized Fields
    - bias
```
double bias
```
      The initial offset value that the ensemble outputs are added to.
- Class gov.sandia.cognition.learning.algorithm.ensemble.AveragingEnsemble extends AbstractUnweightedEnsemble<MemberType extends Evaluator<? super InputType,? extends java.lang.Number>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner extends AbstractBaggingLearner<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner.OutOfBagErrorStoppingCriteria extends AbstractCategorizerOutOfBagStoppingCriteria<InputType,CategoryType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.ensemble.BaggingRegressionLearner extends AbstractBaggingLearner<InputType,java.lang.Double,Evaluator<? super InputType,? extends java.lang.Number>,AveragingEnsemble<InputType,Evaluator<? super InputType,? extends java.lang.Number>>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.ensemble.BinaryBaggingLearner extends AbstractBaggingLearner<InputType,java.lang.Boolean,Evaluator<? super InputType,? extends java.lang.Boolean>,WeightedBinaryEnsemble<InputType,Evaluator<? super InputType,? extends java.lang.Boolean>>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.ensemble.BinaryCategorizerSelector extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - categorizers
```
java.util.Collection<E> categorizers
```
      The collection of categorizers to evaluate and select from.
- Class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedBaggingLearner extends BaggingCategorizerLearner<InputType,CategoryType> implements Serializable
  - Serialized Fields
    - categoryList
```
java.util.ArrayList<E> categoryList
```
      The list of categories.
    - dataPerCategory
```
java.util.HashMap<K,V> dataPerCategory
```
      The mapping of categories to indices of examples belonging to the category.
- Class gov.sandia.cognition.learning.algorithm.ensemble.CategoryBalancedIVotingLearner extends IVotingCategorizerLearner<InputType,CategoryType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner extends AbstractAnytimeSupervisedBatchLearner<InputType,CategoryType,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>> implements Serializable
  - Serialized Fields
    - learner
```
BatchLearner<DataType,ResultType> learner
```
      The learner used to produce each ensemble member.
    - percentToSample
```
double percentToSample
```
      The percent to sample on each iteration.
    - proportionIncorrectInSample
```
double proportionIncorrectInSample
```
      The proportion of incorrect examples in each sample. Must be between 0.0 and 1.0 (inclusive).
    - voteOutOfBagOnly
```
boolean voteOutOfBagOnly
```
      Controls whether or not an ensemble member can vote on items it was trained on during learning. By default, the ensemble member can only vote on out-of-bag values.
    - counterFactory
```
Factory<CreatedType> counterFactory
```
      Factory for counting votes.
    - random
```
java.util.Random random
```
      The random number generator to use.
- Class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner.OutOfBagErrorStoppingCriteria extends AbstractCategorizerOutOfBagStoppingCriteria<InputType,CategoryType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.ensemble.MultiCategoryAdaBoost extends AbstractAnytimeSupervisedBatchLearner<InputType,CategoryType,WeightedVotingCategorizerEnsemble<InputType,CategoryType,Evaluator<? super InputType,? extends CategoryType>>> implements Serializable
  - Serialized Fields
    - weakLearner
```
BatchLearner<DataType,ResultType> weakLearner
```
      The "weak learner" that must learn from the weighted input-output pairs on each iteration.
- Class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner extends AbstractSupervisedBatchAndIncrementalLearner<InputType,CategoryType,VotingCategorizerEnsemble<InputType,CategoryType,MemberType extends Evaluator<? super InputType,? extends CategoryType>>> implements Serializable
  - Serialized Fields
    - learner
```
IncrementalLearner<DataType,ResultType> learner
```
      The base learner used for each ensemble member.
    - ensembleSize
```
int ensembleSize
```
      The size of the ensemble to create. Must be positive.
    - percentToSample
```
double percentToSample
```
      The percentage of the data to sample for each ensemble member. Must be positive. Used as a parameter to the Poisson distribution to determine the number of samples for each ensemble member.
    - random
```
java.util.Random random
```
      The random number generator to use.
- Class gov.sandia.cognition.learning.algorithm.ensemble.VotingCategorizerEnsemble extends AbstractDiscriminantCategorizer<InputType,CategoryType,java.lang.Double> implements Serializable
  - Serialized Fields
    - members
```
java.util.List<E> members
```
      The members of the ensemble.
- Class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAdditiveEnsemble extends AbstractWeightedEnsemble<MemberType extends Evaluator<? super InputType,? extends java.lang.Number>> implements Serializable
  - Serialized Fields
    - bias
```
double bias
```
      The initial offset value that the ensemble outputs are added to.
- Class gov.sandia.cognition.learning.algorithm.ensemble.WeightedAveragingEnsemble extends AbstractWeightedEnsemble<MemberType extends Evaluator<? super InputType,? extends java.lang.Number>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.ensemble.WeightedBinaryEnsemble extends AbstractDiscriminantBinaryCategorizer<InputType> implements Serializable
  - Serialized Fields
    - members
```
java.util.List<E> members
```
      The members of the ensemble.
- Class gov.sandia.cognition.learning.algorithm.ensemble.WeightedVotingCategorizerEnsemble extends AbstractCategorizer<InputType,CategoryType> implements Serializable
  - Serialized Fields
    - members
```
java.util.List<E> members
```
      The members of the ensemble.
Package gov.sandia.cognition.learning.algorithm.factor.machine
- Class gov.sandia.cognition.learning.algorithm.factor.machine.AbstractFactorizationMachineLearner extends AbstractAnytimeSupervisedBatchLearner<Vector,java.lang.Double,FactorizationMachine> implements Serializable
  - Serialized Fields
    - biasEnabled
```
boolean biasEnabled
```
      True if the bias term is enabled.
    - weightsEnabled
```
boolean weightsEnabled
```
      True if the linear weight term is enabled.
    - factorCount
```
int factorCount
```
      The number of factors to use. Zero means no factors.
    - biasRegularization
```
double biasRegularization
```
      The regularization term for the bias. Cannot be negative.
    - weightRegularization
```
double weightRegularization
```
      The regularization term for the linear weights. Cannot be negative.
    - factorRegularization
```
double factorRegularization
```
      The regularization term for the factor matrix. Cannot be negative.
    - seedScale
```
double seedScale
```
      The standard deviation for initializing the factors. Cannot be negative.
    - random
```
java.util.Random random
```
      The random number generator to use.
- Class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachine extends AbstractRegressor<Vector> implements Serializable
  - Serialized Fields
    - bias
```
double bias
```
      The bias term (b).
    - weights
```
Vector weights
```
      The weight vector (w) for each dimension.
    - factors
```
Matrix factors
```
      The k x d factor matrix (v) with k factors for each dimension. May be null.
- Class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineAlternatingLeastSquares extends AbstractFactorizationMachineLearner implements Serializable
  - Serialized Fields
    - minChange
```
double minChange
```
      The minimum change allowed in an iteration. The algorithm stops if the change is less than this value. Cannot be negative.
    - totalChange
```
double totalChange
```
      The total change from the current iteration.
    - totalError
```
double totalError
```
      The total error from the current iteration.
- Class gov.sandia.cognition.learning.algorithm.factor.machine.FactorizationMachineStochasticGradient extends AbstractFactorizationMachineLearner implements Serializable
  - Serialized Fields
    - learningRate
```
double learningRate
```
      The learning rate for the algorithm. Must be positive.
Package gov.sandia.cognition.learning.algorithm.genetic
- Class gov.sandia.cognition.learning.algorithm.genetic.EvaluatedGenome extends java.lang.Object implements Serializable
  - Serialized Fields
    - genome
```
java.lang.Object genome
```
      The genome that was evaluated.
    - cost
```
double cost
```
      The cost associated with a Genome.
- Class gov.sandia.cognition.learning.algorithm.genetic.GeneticAlgorithm extends AbstractAnytimeBatchLearner<CostParametersType,GenomeType> implements Serializable
  - Serialized Fields
    - costFunction
```
CostFunction<EvaluatedType,CostParametersType> costFunction
```
      The cost function for genomes.
    - reproducer
```
Reproducer<GenomeType> reproducer
```
      The reproduction function for genomes.
    - bestSoFar
```
EvaluatedGenome<GenomeType> bestSoFar
```
      The best genome found so far.
    - maxIterationsWithoutImprovement
```
int maxIterationsWithoutImprovement
```
      The maximum number of iterations to go without improvement before stopping
    - iterationsWithoutImprovement
```
int iterationsWithoutImprovement
```
      The number of iterations since the last improvement.
    - population
```
java.util.Collection<E> population
```
      The population of genomes.
    - initialPopulation
```
java.util.Collection<E> initialPopulation
```
      The initial population of genomes
- Class gov.sandia.cognition.learning.algorithm.genetic.ParallelizedGeneticAlgorithm extends GeneticAlgorithm<CostParametersType,GenomeType> implements Serializable
  - Serialized Fields
    - evaluateTasks
```
java.util.ArrayList<E> evaluateTasks
```
      Parallel tasks that evaluate genome fitness
Package gov.sandia.cognition.learning.algorithm.genetic.reproducer
- Class gov.sandia.cognition.learning.algorithm.genetic.reproducer.CrossoverReproducer extends java.lang.Object implements Serializable
  - Serialized Fields
    - selector
```
Selector<GenomeType> selector
```
      The selector to use to select the population.
    - crossoverFunction
```
CrossoverFunction<GenomeType> crossoverFunction
```
      The crossover function to use.
- Class gov.sandia.cognition.learning.algorithm.genetic.reproducer.MultiReproducer extends java.lang.Object implements Serializable
  - Serialized Fields
    - reproducers
```
java.util.Collection<E> reproducers
```
      The reproducers to use for reproducing.
- Class gov.sandia.cognition.learning.algorithm.genetic.reproducer.MutationReproducer extends java.lang.Object implements Serializable
  - Serialized Fields
    - perturber
```
Perturber<PerturbedType> perturber
```
      The perturber to use for mutation.
    - selector
```
Selector<GenomeType> selector
```
      The selector to use to select the population.
- Class gov.sandia.cognition.learning.algorithm.genetic.reproducer.VectorizableCrossoverFunction extends AbstractRandomized implements Serializable
  - Serialized Fields
    - probabilityCrossover
```
double probabilityCrossover
```
      Probability that an element in the child will come from vector2, and with probability (1-probabilityCrossover) the element will come from vector1. Thus, probabilityCrossover==0.0 means that all elements will come from vector1 and probabilityCrossover==1.0 means that all elements will come from vector2, probabilityCrossover==0.5 has maximum entropy in terms of where the elements of the child vector came from
Package gov.sandia.cognition.learning.algorithm.genetic.selector
- Class gov.sandia.cognition.learning.algorithm.genetic.selector.AbstractSelector extends java.lang.Object implements Serializable
- Class gov.sandia.cognition.learning.algorithm.genetic.selector.TournamentSelector extends AbstractSelector<GenomeType> implements Serializable
  - Serialized Fields
    - percent
```
double percent
```
      The percent of the population to select.
    - tournamentSize
```
int tournamentSize
```
      The size of the tournament.
    - random
```
java.util.Random random
```
      The random number generator to use.
Package gov.sandia.cognition.learning.algorithm.gradient
- Class gov.sandia.cognition.learning.algorithm.gradient.GradientDescendableApproximator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - deltaSize
```
double deltaSize
```
      Size of the finite-difference unit vectors, typically ~1e-5
    - function
```
VectorizableVectorFunction function
```
      Internal VectorizableVectorFunction to consider
Package gov.sandia.cognition.learning.algorithm.hmm
- Class gov.sandia.cognition.learning.algorithm.hmm.AbstractBaumWelchAlgorithm extends AbstractAnytimeBatchLearner<DataType,HiddenMarkovModel<ObservationType>> implements Serializable
  - Serialized Fields
    - distributionLearner
```
BatchLearner<DataType,ResultType> distributionLearner
```
      Learner for the Distribution Functions of the HMM.
    - result
```
HiddenMarkovModel<ObservationType> result
```
      Result of the Baum-Welch Algorithm
    - initialGuess
```
HiddenMarkovModel<ObservationType> initialGuess
```
      Initial guess for the iterations.
    - lastLogLikelihood
```
double lastLogLikelihood
```
      Last Log Likelihood of the iterations
    - reestimateInitialProbabilities
```
boolean reestimateInitialProbabilities
```
      Flag to re-estimate the initial probability Vector.
- Class gov.sandia.cognition.learning.algorithm.hmm.BaumWelchAlgorithm extends AbstractBaumWelchAlgorithm<ObservationType,java.util.Collection<? extends ObservationType>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.hmm.HiddenMarkovModel extends MarkovChain implements Serializable
  - Serialized Fields
    - emissionFunctions
```
java.util.Collection<E> emissionFunctions
```
      The PDFs that emit symbols from each state.
- Class gov.sandia.cognition.learning.algorithm.hmm.MarkovChain extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - initialProbability
```
Vector initialProbability
```
      Initial probability Vector over the states. Each entry must be nonnegative and the Vector must sum to 1.
    - transitionProbability
```
Matrix transitionProbability
```
      Transition probability matrix. The entry (i,j) is the probability of transition from state "j" to state "i". As a corollary, all entries in the Matrix must be nonnegative and the columns of the Matrix must sum to 1.
- Class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm extends BaumWelchAlgorithm<ObservationType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.hmm.ParallelBaumWelchAlgorithm.DistributionEstimatorTask extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - weightedValues
```
java.util.ArrayList<E> weightedValues
```
      Weighted values for the PDF estimator.
    - distributionLearner
```
BatchLearner<DataType,ResultType> distributionLearner
```
      My copy of the PDF estimator.
    - gammas
```
java.util.ArrayList<E> gammas
```
      Gammas used to weight the learner samples.
    - index
```
int index
```
      Index into the gammas to pull the weights.
- Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel extends HiddenMarkovModel<ObservationType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ComputeTransitionsTask extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - alphan
```
Vector alphan
```
      Alpha at time n.
    - betanp1
```
Vector betanp1
```
      Alpha at time n.
    - bnp1
```
Vector bnp1
```
      b at time n+1.
- Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.LogLikelihoodTask extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - data
```
java.util.Collection<E> data
```
      Data to compute the log-likelihood of
- Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.NormalizeTransitionTask extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - A
```
Matrix A
```
      Matrix to normalize.
    - j
```
int j
```
      Column to normalize.
- Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ObservationLikelihoodTask extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - observations
```
java.util.Collection<E> observations
```
      Observations
    - distributionFunction
```
ProbabilityFunction<DataType> distributionFunction
```
      The PDF.
- Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.StateObservationLikelihoodTask extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - alpha
```
Vector alpha
```
      Alpha at time n.
    - beta
```
Vector beta
```
      Beta at time n.
- Class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ViterbiTask extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - destinationState
```
int destinationState
```
      Destination state for the Viterbi Recursion.
    - delta
```
Vector delta
```
      Previous value of the Viterbi Recursion.
Package gov.sandia.cognition.learning.algorithm.minimization
- Class gov.sandia.cognition.learning.algorithm.minimization.AbstractAnytimeFunctionMinimizer extends AbstractAnytimeBatchLearner<EvaluatorType extends Evaluator<? super InputType,? extends OutputType>,InputOutputPair<InputType,OutputType>> implements Serializable
  - Serialized Fields
    - tolerance
```
double tolerance
```
      Tolerance of the minimization algorithm, must be >= 0.0
    - result
```
InputOutputPair<InputType,OutputType> result
```
      Resulting minimum input-output pair
    - initialGuess
```
java.lang.Object initialGuess
```
      Initial guess of the minimization routine
- Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerBFGS extends FunctionMinimizerQuasiNewton implements Serializable
- Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerConjugateGradient extends AbstractAnytimeFunctionMinimizer<Vector,java.lang.Double,DifferentiableEvaluator<? super Vector,java.lang.Double,Vector>> implements Serializable
  - Serialized Fields
    - lineMinimizer
```
LineMinimizer<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>> lineMinimizer
```
      Work-horse algorithm that minimizes the function along a direction
    - lineFunction
```
DirectionalVectorToDifferentiableScalarFunction lineFunction
```
      Function that maps a Evaluator onto a Evaluator using a set point, direction and scale factor
    - gradient
```
Vector gradient
```
      Gradient at the current guess
- Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerDFP extends FunctionMinimizerQuasiNewton implements Serializable
- Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerDirectionSetPowell extends AbstractAnytimeFunctionMinimizer<Vector,java.lang.Double,Evaluator<? super Vector,java.lang.Double>> implements Serializable
  - Serialized Fields
    - lineMinimizer
```
LineMinimizer<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>> lineMinimizer
```
      Work-horse algorithm that minimizes the function along a direction
    - directionSet
```
java.util.List<E> directionSet
```
      Matrix where the columns indicate the directions of minimization
    - lineFunction
```
DirectionalVectorToScalarFunction lineFunction
```
      Function that maps a Evaluator onto a Evaluator using a set point, direction and scale factor
- Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerFletcherReeves extends FunctionMinimizerConjugateGradient implements Serializable
- Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerGradientDescent extends AbstractAnytimeFunctionMinimizer<Vector,java.lang.Double,DifferentiableEvaluator<? super Vector,java.lang.Double,Vector>> implements Serializable
  - Serialized Fields
    - learningRate
```
double learningRate
```
      The learning rate (or step size), must be (0,1], typically ~0.1
    - momentum
```
double momentum
```
      The momentum rate, must be [0,1), typically ~0.8
    - previousDelta
```
Vector previousDelta
```
      Previous input change, used for adding momentum
- Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerLiuStorey extends FunctionMinimizerConjugateGradient implements Serializable
- Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerNelderMead extends AbstractAnytimeFunctionMinimizer<Vector,java.lang.Double,Evaluator<? super Vector,java.lang.Double>> implements Serializable
  - Serialized Fields
    - simplex
```
java.util.ArrayList<E> simplex
```
      InputOutputPairs that define the simplex
    - simplexInputSum
```
Vector simplexInputSum
```
      A running sum of the inputs of the simplex, used for reflection
    - lineFunction
```
DirectionalVectorToScalarFunction lineFunction
```
      Function that defines the simplex growth direction
- Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerPolakRibiere extends FunctionMinimizerConjugateGradient implements Serializable
- Class gov.sandia.cognition.learning.algorithm.minimization.FunctionMinimizerQuasiNewton extends AbstractAnytimeFunctionMinimizer<Vector,java.lang.Double,DifferentiableEvaluator<? super Vector,java.lang.Double,Vector>> implements Serializable
  - Serialized Fields
    - lineMinimizer
```
LineMinimizer<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>> lineMinimizer
```
      Work-horse algorithm that minimizes the function along a direction
    - lineFunction
```
DirectionalVectorToDifferentiableScalarFunction lineFunction
```
      Function that maps a Evaluator onto a Evaluator using a set point, direction and scale factor
    - hessianInverse
```
Matrix hessianInverse
```
      Estimated inverse of the Hessian (second derivative)
    - gradient
```
Vector gradient
```
      Gradient at the current guess
    - dimensionality
```
int dimensionality
```
      The dimensionality of the input space
Package gov.sandia.cognition.learning.algorithm.minimization.line
- Class gov.sandia.cognition.learning.algorithm.minimization.line.AbstractAnytimeLineMinimizer extends AbstractAnytimeFunctionMinimizer<java.lang.Double,java.lang.Double,EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>> implements Serializable
  - Serialized Fields
    - bracket
```
LineBracket bracket
```
      LineBracket bounding a local minimum.
    - validBracket
```
boolean validBracket
```
      Flag indicating if the algorithm has already found a valid bracket on a local minimum.
    - interpolator
```
LineBracketInterpolator<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>> interpolator
```
      Type of algorithm to fit data points and find an interpolated minimum to the known points.
    - initialGuessFunctionValue
```
java.lang.Double initialGuessFunctionValue
```
      Function value at the initialGuess, may be null.
    - initialGuessSlope
```
java.lang.Double initialGuessSlope
```
      Function slope at the initialGuess, may be null.
- Class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToDifferentiableScalarFunction extends DirectionalVectorToScalarFunction implements Serializable
  - Serialized Fields
    - lastGradient
```
InputOutputPair<InputType,OutputType> lastGradient
```
      Last gradient information
- Class gov.sandia.cognition.learning.algorithm.minimization.line.DirectionalVectorToScalarFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - vectorOffset
```
Vector vectorOffset
```
      Vector offset to scale in the specified direction
    - direction
```
Vector direction
```
      Directional vector for optimization
    - vectorScalarFunction
```
Evaluator<InputType,OutputType> vectorScalarFunction
```
      Function that maps a Vector onto a Double
    - lastEvaluation
```
DefaultInputOutputPair<InputType,OutputType> lastEvaluation
```
      Cache for the last input/output that was evaluated, so that we can avoid using it again in the differentiate method.
- Class gov.sandia.cognition.learning.algorithm.minimization.line.InputOutputSlopeTriplet extends DefaultInputOutputPair<java.lang.Double,java.lang.Double> implements Serializable
  - Serialized Fields
    - slope
```
java.lang.Double slope
```
      Slope (first derivative) at the given point
- Class gov.sandia.cognition.learning.algorithm.minimization.line.LineBracket extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - lowerBound
```
InputOutputSlopeTriplet lowerBound
```
      Lower bound of the bracket.
    - upperBound
```
InputOutputSlopeTriplet upperBound
```
      Upper bound of the bracket.
    - otherPoint
```
InputOutputSlopeTriplet otherPoint
```
      Another (optional) point associated with the bracket.
- Class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerBacktracking extends AbstractAnytimeLineMinimizer<Evaluator<java.lang.Double,java.lang.Double>> implements Serializable
  - Serialized Fields
    - sufficientDecrease
```
double sufficientDecrease
```
      Sufficient decrease condition, must be (0,1). Smaller values (0.1) result in more accurate searches, larger values (0.9) tend to be easier to satisfy.
    - geometricDecrease
```
double geometricDecrease
```
      Amount to decrease the step amount each iteration.
    - numericalDerivative
```
boolean numericalDerivative
```
      Flag whether or not to use the numerical differentiation.
    - stepValue
```
double stepValue
```
      Current value of the step size.
- Class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased extends AbstractAnytimeLineMinimizer<DifferentiableUnivariateScalarFunction> implements Serializable
  - Serialized Fields
    - minFunctionValue
```
double minFunctionValue
```
      Minimum value of the target function. In other words, the user will accept a solution less than or equal to minFunctionValue. For many applications 0.0 is a likely candidate (for cost functions, metrics, least squares, etc.)
    - direction
```
double direction
```
      Direction of the search. Because Fletcher assumes the slope of the initialGuess is less than 0.0, we have to flip around the direction of search if the initial guess has positive slope. Thus, direction=1.0 means that the initial slope was negative, while direction=-1.0 means that the initial slope was positive.
    - internalFunction
```
LineMinimizerDerivativeBased.InternalFunction internalFunction
```
      Internal function used to map/remap/unmap the search direction.
    - wolfe
```
WolfeConditions wolfe
```
      The Wolfe conditions define approximate line search stopping criteria.
    - maxX
```
double maxX
```
      Maximum value of x in the search space. That is, the minimizer will not be greater than maxX.
- Class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeBased.InternalFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
- Class gov.sandia.cognition.learning.algorithm.minimization.line.LineMinimizerDerivativeFree extends AbstractAnytimeLineMinimizer<Evaluator<java.lang.Double,java.lang.Double>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.minimization.line.WolfeConditions extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - originalPoint
```
InputOutputSlopeTriplet originalPoint
```
      Original point to store, slope must be less than 0.0.
    - slopeCondition
```
double slopeCondition
```
      Slope condition parameter for the Goldstein condition, must be less than curvatureCondition and on the interval (0,1).
    - curvatureCondition
```
double curvatureCondition
```
      Curvature condition for the curvature condition, must be greater than slopeCondition and on the interval (0,1).
Package gov.sandia.cognition.learning.algorithm.minimization.line.interpolator
- Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.AbstractLineBracketInterpolator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - tolerance
```
double tolerance
```
      Tolerance of the interpolator to collinear or identical points
- Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.AbstractLineBracketInterpolatorPolynomial extends AbstractLineBracketInterpolator<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorBrent extends AbstractLineBracketInterpolator<Evaluator<java.lang.Double,java.lang.Double>> implements Serializable
  - Serialized Fields
    - parabolicInterpolator
```
LineBracketInterpolatorParabola parabolicInterpolator
```
      Non-slope based parabolic interpolator.
    - goldenInterpolator
```
LineBracketInterpolatorGoldenSection goldenInterpolator
```
      Golden-section step interpolator.
- Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorGoldenSection extends AbstractLineBracketInterpolator<Evaluator<java.lang.Double,java.lang.Double>> implements Serializable
  - Serialized Fields
    - linearInterpolator
```
LineBracketInterpolatorLinear linearInterpolator
```
      Back-up interpolator using the secant method.
- Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorHermiteCubic extends AbstractLineBracketInterpolatorPolynomial<DifferentiableUnivariateScalarFunction> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorHermiteParabola extends AbstractLineBracketInterpolatorPolynomial<DifferentiableUnivariateScalarFunction> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorLinear extends AbstractLineBracketInterpolatorPolynomial<Evaluator<java.lang.Double,java.lang.Double>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.minimization.line.interpolator.LineBracketInterpolatorParabola extends AbstractLineBracketInterpolatorPolynomial<Evaluator<java.lang.Double,java.lang.Double>> implements Serializable
Package gov.sandia.cognition.learning.algorithm.minimization.matrix
- Class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientMatrixSolver extends IterativeMatrixSolver<MatrixVectorMultiplier> implements Serializable
  - Serialized Fields
    - A
```
MatrixVectorMultiplier A
```
      The matrix vector multiplier
    - residual
```
Vector residual
```
      The per-iteration residual
    - d
```
Vector d
```
      The conjugated direction vector
    - x
```
Vector x
```
      The current best estimate for x
    - delta
```
double delta
```
      A cross-iteration variable
- Class gov.sandia.cognition.learning.algorithm.minimization.matrix.ConjugateGradientWithPreconditionerMatrixSolver extends IterativeMatrixSolver<MatrixVectorMultiplierWithPreconditioner> implements Serializable
  - Serialized Fields
    - A
```
MatrixVectorMultiplierWithPreconditioner A
```
      The matrix vector multiplier
    - residual
```
Vector residual
```
      The per-iteration residual
    - d
```
Vector d
```
      The conjugated direction vector
    - x
```
Vector x
```
      The current best estimate for x
    - delta
```
double delta
```
      A cross-iteration variable
- Class gov.sandia.cognition.learning.algorithm.minimization.matrix.IterativeMatrixSolver extends java.lang.Object implements Serializable
  - Serialized Fields
    - tolerance
```
double tolerance
```
      The tolerance of the error accepted before stopping iterations.
    - x0
```
Vector x0
```
      The initial guess for the left-hand-side vector (x).
    - rhs
```
Vector rhs
```
      The right-hand-side vector (b).
    - maxIterations
```
int maxIterations
```
      Execution will stop after this number of iterations even if it has not converged.
    - listeners
```
java.util.Set<E> listeners
```
      Listeners to the algorithms progress have the opportunity to stop the algorithm after a specified number of iterations.
    - iterationCounter
```
int iterationCounter
```
      Counts the number of iterations executed thus far.
    - shouldStop
```
boolean shouldStop
```
      If set to true, the algorithm will stop after the current iteration completes.
    - result
```
InputOutputPair<InputType,OutputType> result
```
      Stores the input rhs vector and the resulting x vector from the most recent "learn" call.
- Class gov.sandia.cognition.learning.algorithm.minimization.matrix.OverconstrainedConjugateGradientMatrixMinimizer extends IterativeMatrixSolver<OverconstrainedMatrixVectorMultiplier> implements Serializable
  - Serialized Fields
    - A
```
OverconstrainedMatrixVectorMultiplier A
```
      The matrix vector multiplier
    - residual
```
Vector residual
```
      The per-iteration residual
    - d
```
Vector d
```
      The conjugated direction vector
    - x
```
Vector x
```
      The current best estimate for x
    - delta
```
double delta
```
      A cross-iteration variable
    - AtransB
```
Vector AtransB
```
      My A^T*b right-hand-side vector
- Class gov.sandia.cognition.learning.algorithm.minimization.matrix.SteepestDescentMatrixSolver extends IterativeMatrixSolver<MatrixVectorMultiplier> implements Serializable
  - Serialized Fields
    - A
```
MatrixVectorMultiplier A
```
      The matrix vector multiplier
    - residual
```
Vector residual
```
      The per-iteration residual
    - x
```
Vector x
```
      The current best estimate for x
    - delta
```
double delta
```
      A cross-iteration variable
Package gov.sandia.cognition.learning.algorithm.nearest
- Class gov.sandia.cognition.learning.algorithm.nearest.AbstractKNearestNeighbor extends AbstractNearestNeighbor<InputType,OutputType> implements Serializable
  - Serialized Fields
    - k
```
int k
```
      Number of neighbors to consider, must be greater than zero
    - averager
```
Summarizer<DataType,SummaryType> averager
```
      Creates a single object from a collection of data
- Class gov.sandia.cognition.learning.algorithm.nearest.AbstractNearestNeighbor extends DefaultDivergenceFunctionContainer<InputType,InputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive extends AbstractKNearestNeighbor<InputType,OutputType> implements Serializable
  - Serialized Fields
    - data
```
java.util.Collection<E> data
```
      Underlying data for the classifier
- Class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive.Learner extends KNearestNeighborExhaustive<InputType,OutputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive.Neighbor extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - value
```
java.lang.Object value
```
      Output value.
    - divergence
```
double divergence
```
      Divergence associated with this value.
- Class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborKDTree extends AbstractKNearestNeighbor<InputType extends Vectorizable,OutputType> implements Serializable
  - Serialized Fields
    - data
```
KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> data
```
      KDTree that holds the data to search for neighbors.
- Class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborKDTree.Learner extends KNearestNeighborKDTree<InputType extends Vectorizable,OutputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborExhaustive extends AbstractNearestNeighbor<InputType,OutputType> implements Serializable
  - Serialized Fields
    - data
```
java.util.LinkedList<E> data
```
      The data that nearest-neighbor is performed over.
- Class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborExhaustive.Learner extends DefaultDivergenceFunctionContainer<InputType,InputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborKDTree extends AbstractNearestNeighbor<InputType extends Vectorizable,OutputType> implements Serializable
  - Serialized Fields
    - data
```
KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> data
```
      KDTree that holds the data to search for neighbors.
- Class gov.sandia.cognition.learning.algorithm.nearest.NearestNeighborKDTree.Learner extends NearestNeighborKDTree<InputType extends Vectorizable,OutputType> implements Serializable
Package gov.sandia.cognition.learning.algorithm.pca
- Class gov.sandia.cognition.learning.algorithm.pca.AbstractPrincipalComponentsAnalysis extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - numComponents
```
int numComponents
```
      Number of components to extract from the data, must be greater than zero
    - result
```
PrincipalComponentsAnalysisFunction result
```
      Vector function that maps the input space onto a numComponents-dimension Vector representing the directions of maximal variance (information gain). The i-th row in the matrix approximates the i-th column of the "U" matrix of the Singular Value Decomposition.
- Class gov.sandia.cognition.learning.algorithm.pca.GeneralizedHebbianAlgorithm extends AbstractAnytimeBatchLearner<java.util.Collection<Vector>,PrincipalComponentsAnalysisFunction> implements Serializable
  - Serialized Fields
    - learningRate
```
double learningRate
```
      Learning rate, or step size, (0,1], typically ~0.1
    - numComponents
```
int numComponents
```
      Number of components to extract from the data, must be greater than zero
    - result
```
PrincipalComponentsAnalysisFunction result
```
      Vector function that maps the input space onto a numComponents-dimension Vector representing the directions of maximal variance (information gain). The i-th row in the matrix approximates the i-th column of the "U" matrix of the Singular Value Decomposition.
    - components
```
java.util.ArrayList<E> components
```
      Components that have been extracted from the input data, each component has the same dimensions as the input data and the size of the ArrayList is numComponents
    - mean
```
Vector mean
```
      Sample mean of the training data. This is subtracted from the training data before GHA is executed.
    - minChange
```
double minChange
```
      Minimum change below which to stop iterating, greater than or equal to zero, typically 1e-10
- Class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis extends DefaultKernelContainer<DataType> implements Serializable
  - Serialized Fields
    - componentCount
```
int componentCount
```
      The number of components to create from the analysis. Must be positive.
    - centerData
```
boolean centerData
```
      Whether or not the data should be centered before doing KPCA.
- Class gov.sandia.cognition.learning.algorithm.pca.KernelPrincipalComponentsAnalysis.Function extends DefaultKernelContainer<DataType> implements Serializable
  - Serialized Fields
    - data
```
java.util.List<E> data
```
      The data that the KPCA was performed over. Each one corresponds to a column in the components matrix.
    - components
```
Matrix components
```
      The matrix of components for the function. The number of rows is the dimensionality of the reduction. The number of columns is equal to the number of data points that the KPCA was done over.
    - centerData
```
boolean centerData
```
      A flag indicating if the incoming data needs to be centered or not. Unless the data is being pre-centered, this should be true.
    - kernelMatrix
```
Matrix kernelMatrix
```
      The kernel matrix for all the data the KPCA was done over. It is a square matrix whose size is equal to the data.
- Class gov.sandia.cognition.learning.algorithm.pca.PrincipalComponentsAnalysisFunction extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - mean
```
Vector mean
```
      Sample mean of the data, which is subtracted from input data to yield zero-mean inputs
    - dimensionReducer
```
MultivariateDiscriminant dimensionReducer
```
      Function that maps a high-dimension input space onto a (hopefully) simple low-dimensional output space capturing the directions of maximum variance (information gain)
- Class gov.sandia.cognition.learning.algorithm.pca.ThinSingularValueDecomposition extends AbstractPrincipalComponentsAnalysis implements Serializable
Package gov.sandia.cognition.learning.algorithm.perceptron
- Class gov.sandia.cognition.learning.algorithm.perceptron.AbstractKernelizableBinaryCategorizerOnlineLearner extends AbstractOnlineLinearBinaryCategorizerLearner implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.AbstractLinearCombinationOnlineLearner extends AbstractKernelizableBinaryCategorizerOnlineLearner implements Serializable
  - Serialized Fields
    - updateBias
```
boolean updateBias
```
      An option controlling whether or not the bias is updated or not. Individual algorithm implementations choose the default value for this.
- Class gov.sandia.cognition.learning.algorithm.perceptron.AbstractOnlineLinearBinaryCategorizerLearner extends AbstractSupervisedBatchAndIncrementalLearner<Vectorizable,java.lang.Boolean,LinearBinaryCategorizer> implements Serializable
  - Serialized Fields
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The factory to create weight vectors.
- Class gov.sandia.cognition.learning.algorithm.perceptron.AggressiveRelaxedOnlineMaximumMarginAlgorithm extends AbstractKernelizableBinaryCategorizerOnlineLearner implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.Ballseptron extends AbstractKernelizableBinaryCategorizerOnlineLearner implements Serializable
  - Serialized Fields
    - radius
```
double radius
```
      The radius enforced by the algorithm.
- Class gov.sandia.cognition.learning.algorithm.perceptron.BatchMultiPerceptron extends AbstractAnytimeSupervisedBatchLearner<Vectorizable,CategoryType,LinearMultiCategorizer<CategoryType>> implements Serializable
  - Serialized Fields
    - minMargin
```
double minMargin
```
      The minimum margin to enforce. Must be non-negative.
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The factory to create weight vectors.
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm extends AbstractLinearCombinationOnlineLearner implements Serializable
  - Serialized Fields
    - minMargin
```
double minMargin
```
      The minimum margin to enforce. Must be non-negative.
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron extends AbstractBatchAndIncrementalLearner<InputOutputPair<? extends Vectorizable,CategoryType>,LinearMultiCategorizer<CategoryType>> implements Serializable
  - Serialized Fields
    - minMargin
```
double minMargin
```
      The minimum margin to enforce. Must be non-negative.
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The factory to create weight vectors.
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron.ProportionalUpdate extends OnlineMultiPerceptron<CategoryType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron.UniformUpdate extends OnlineMultiPerceptron<CategoryType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron extends AbstractLinearCombinationOnlineLearner implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.AbstractSoftMargin extends OnlinePassiveAggressivePerceptron implements Serializable
  - Serialized Fields
    - aggressiveness
```
double aggressiveness
```
      The aggressiveness parameter (C), which is the trade-off between aggressive updating to meet an incorrect example and keeping history around.
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.LinearSoftMargin extends OnlinePassiveAggressivePerceptron.AbstractSoftMargin implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron.QuadraticSoftMargin extends OnlinePassiveAggressivePerceptron.AbstractSoftMargin implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePerceptron extends AbstractLinearCombinationOnlineLearner implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineRampPassiveAggressivePerceptron extends OnlinePassiveAggressivePerceptron.QuadraticSoftMargin implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron extends AbstractLinearCombinationOnlineLearner implements Serializable
  - Serialized Fields
    - lambda
```
double lambda
```
      The lambda parameter for controlling how much shifting occurs.
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron.LinearResult extends LinearBinaryCategorizer implements Serializable
  - Serialized Fields
    - errorCount
```
long errorCount
```
      The number of errors made by the categorizer so far.
- Class gov.sandia.cognition.learning.algorithm.perceptron.OnlineVotedPerceptron extends AbstractSupervisedBatchAndIncrementalLearner<Vectorizable,java.lang.Boolean,WeightedBinaryEnsemble<Vectorizable,LinearBinaryCategorizer>> implements Serializable
  - Serialized Fields
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The factory to create weight vectors.
- Class gov.sandia.cognition.learning.algorithm.perceptron.Perceptron extends AbstractAnytimeSupervisedBatchLearner<Vectorizable,java.lang.Boolean,LinearBinaryCategorizer> implements Serializable
  - Serialized Fields
    - marginPositive
```
double marginPositive
```
      The positive margin to enforce.
    - marginNegative
```
double marginNegative
```
      The negative margin to enforce.
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The VectorFactory to use to create vectors.
    - result
```
LinearBinaryCategorizer result
```
      The result categorizer.
    - errorCount
```
int errorCount
```
      The number of errors on the most recent iteration.
- Class gov.sandia.cognition.learning.algorithm.perceptron.RelaxedOnlineMaximumMarginAlgorithm extends AbstractKernelizableBinaryCategorizerOnlineLearner implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.Winnow extends AbstractOnlineLinearBinaryCategorizerLearner implements Serializable
  - Serialized Fields
    - weightUpdate
```
double weightUpdate
```
      The amount of the weight update (alpha). Must be greater than 1.
    - demoteToZero
```
boolean demoteToZero
```
      An option to demote to zero.
    - weightUpdateInverse
```
double weightUpdateInverse
```
      The cached value of the inverse of weight update (commonly alpha or 1 + epsilon).
Package gov.sandia.cognition.learning.algorithm.perceptron.kernel
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineBudgetedKernelBinaryCategorizerLearner extends AbstractOnlineKernelBinaryCategorizerLearner<InputType> implements Serializable
  - Serialized Fields
    - budget
```
int budget
```
      The budget of the number of examples to keep. Must be positive.
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineKernelBinaryCategorizerLearner extends AbstractSupervisedBatchAndIncrementalLearner<InputType,java.lang.Boolean,DefaultKernelBinaryCategorizer<InputType>> implements Serializable
  - Serialized Fields
    - kernel
```
Kernel<InputType> kernel
```
      The kernel to use.
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron extends AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron.Basic extends AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron.Greedy extends Forgetron<InputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Forgetron.Result extends DefaultKernelBinaryCategorizer<InputType> implements Serializable
  - Serialized Fields
    - errorCount
```
long errorCount
```
      The number of errors that the categorizer has made in the learning step.
    - q
```
double q
```
      The value of Q for the algorithm.
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelAdatron extends AbstractAnytimeSupervisedBatchLearner<InputType,java.lang.Boolean,KernelBinaryCategorizer<InputType,DefaultWeightedValue<InputType>>> implements Serializable
  - Serialized Fields
    - kernel
```
Kernel<InputType> kernel
```
      The kernel to use.
    - result
```
KernelBinaryCategorizer<InputType,EntryType extends WeightedValue<? extends InputType>> result
```
      The result categorizer.
    - errorCount
```
int errorCount
```
      The number of errors on the most recent iteration.
    - supportsMap
```
java.util.LinkedHashMap<K,V> supportsMap
```
      The mapping of weight objects to non-zero weighted examples (support vectors).
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelBinaryCategorizerOnlineLearnerAdapter extends AbstractOnlineKernelBinaryCategorizerLearner<InputType> implements Serializable
  - Serialized Fields
    - learner
```
KernelizableBinaryCategorizerOnlineLearner learner
```
      The wrapped kernelizable learner.
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.KernelPerceptron extends AbstractAnytimeSupervisedBatchLearner<InputType,java.lang.Boolean,DefaultKernelBinaryCategorizer<InputType>> implements Serializable
  - Serialized Fields
    - kernel
```
Kernel<InputType> kernel
```
      The kernel to use.
    - marginPositive
```
double marginPositive
```
      The positive margin to enforce.
    - marginNegative
```
double marginNegative
```
      The negative margin to enforce.
    - result
```
DefaultKernelBinaryCategorizer<InputType> result
```
      The result categorizer.
    - errorCount
```
int errorCount
```
      The number of errors on the most recent iteration.
    - supportsMap
```
java.util.LinkedHashMap<K,V> supportsMap
```
      The mapping of weight objects to non-zero weighted examples (support vectors).
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.OnlineKernelPerceptron extends AbstractOnlineKernelBinaryCategorizerLearner<InputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.OnlineKernelRandomizedBudgetPerceptron extends AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> implements Serializable
  - Serialized Fields
    - random
```
java.util.Random random
```
      The random number generator.
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron extends AbstractOnlineKernelBinaryCategorizerLearner<InputType> implements Serializable
  - Serialized Fields
    - eta
```
double eta
```
      The eta parameter, which ends up controlling the number of supports created. Must be non-negative.
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron.LinearSoftMargin extends Projectron<InputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.RemoveOldestKernelPerceptron extends AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Stoptron extends AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType> implements Serializable
Package gov.sandia.cognition.learning.algorithm.regression
- Class gov.sandia.cognition.learning.algorithm.regression.AbstractLogisticRegression extends AbstractAnytimeSupervisedBatchLearner<InputType,OutputType,FunctionType extends Evaluator<? super InputType,OutputType>> implements Serializable
  - Serialized Fields
    - objectToOptimize
```
Evaluator<InputType,OutputType> objectToOptimize
```
      The object to optimize, used as a factory on successive runs of the algorithm.
    - result
```
Evaluator<InputType,OutputType> result
```
      Return value from the algorithm
    - tolerance
```
double tolerance
```
      Tolerance change in weights before stopping
    - regularization
```
double regularization
```
      L2 ridge regularization term, must be nonnegative, a value of zero is equivalent to unregularized regression.
- Class gov.sandia.cognition.learning.algorithm.regression.AbstractMinimizerBasedParameterCostMinimizer extends AnytimeAlgorithmWrapper<ResultType extends VectorizableVectorFunction,FunctionMinimizer<Vector,java.lang.Double,? super EvaluatorType extends Evaluator<? super Vector,? extends java.lang.Double>>> implements Serializable
  - Serialized Fields
    - objectToOptimize
```
VectorizableVectorFunction objectToOptimize
```
      Object that is being optimized.
    - result
```
VectorizableVectorFunction result
```
      Resulting value
    - costFunction
```
SupervisedCostFunction<InputType,TargetType> costFunction
```
      Cost function to compute the cost of objectToOptimize
- Class gov.sandia.cognition.learning.algorithm.regression.AbstractParameterCostMinimizer extends AbstractAnytimeSupervisedBatchLearner<Vector,Vector,ResultType extends VectorizableVectorFunction> implements Serializable
  - Serialized Fields
    - objectToOptimize
```
VectorizableVectorFunction objectToOptimize
```
      GradientDescendable whose parameters result minimize the cost function
    - result
```
VectorizableVectorFunction result
```
      Result to return
    - tolerance
```
double tolerance
```
      Stopping criterion for the algorithm, typically ~1e-5
    - costFunction
```
SupervisedCostFunction<InputType,TargetType> costFunction
```
      Cost function that computes the cost of the object to optimize
    - resultCost
```
java.lang.Double resultCost
```
      Cost of the result
- Class gov.sandia.cognition.learning.algorithm.regression.FletcherXuHybridEstimation extends LeastSquaresEstimator implements Serializable
  - Serialized Fields
    - lineMinimizer
```
LineMinimizer<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>> lineMinimizer
```
      Workhorse algorithm that finds the minimum along a particular direction
    - reductionTest
```
double reductionTest
```
      Reduction test for switching between BFGS and Levenberg-Marquardt, must be [0,1]. Lower values result in more Levenberg-Marquardt steps, larger values result in more BFGS steps.
    - dampingFactorDivisor
```
double dampingFactorDivisor
```
      Amount to modify the damping factor, typically 2.0 or 10.0
    - lastCost
```
SumSquaredErrorCostFunction.Cache lastCost
```
      Last value of the parameter cost
    - lineFunction
```
DirectionalVectorToDifferentiableScalarFunction lineFunction
```
      Function that maps a Evaluator onto a Evaluator using a set point, direction and scale factor
    - hessianInverse
```
Matrix hessianInverse
```
      Estimated inverse of the Hessian (second derivative)
    - dampingFactor
```
double dampingFactor
```
      Damping factor for the Levenberg-Marquardt ridge regression
- Class gov.sandia.cognition.learning.algorithm.regression.GaussNewtonAlgorithm extends LeastSquaresEstimator implements Serializable
  - Serialized Fields
    - lineMinimizer
```
LineMinimizer<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>> lineMinimizer
```
      Workhorse algorithm that finds the minimum along a particular direction
    - lineFunction
```
DirectionalVectorToDifferentiableScalarFunction lineFunction
```
      Function that maps a Evaluator onto a Evaluator using a set point, direction and scale factor
- Class gov.sandia.cognition.learning.algorithm.regression.KernelBasedIterativeRegression extends AbstractAnytimeSupervisedBatchLearner<InputType,java.lang.Double,KernelScalarFunction<InputType>> implements Serializable
  - Serialized Fields
    - kernel
```
Kernel<InputType> kernel
```
      The kernel to use.
    - minSensitivity
```
double minSensitivity
```
      The bound on sensitivity.
    - result
```
KernelScalarFunction<InputType> result
```
      The result categorizer.
    - errorCount
```
int errorCount
```
      The number of errors on the most recent iteration.
- Class gov.sandia.cognition.learning.algorithm.regression.KernelWeightedRobustRegression extends AbstractAnytimeSupervisedBatchLearner<InputType,OutputType,Evaluator<? super InputType,? extends OutputType>> implements Serializable
  - Serialized Fields
    - result
```
Evaluator<InputType,OutputType> result
```
      DecoupledVectorFunction that is being optimized
    - iterationLearner
```
SupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> iterationLearner
```
      Internal learning algorithm that computes optimal solutions given the current weightedData. The iterationLearner should operate on WeightedInputOutputPairs (we have a hard time enforcing this, as many learning algorithms operate both on InputOutputPairs and WeightedInputOutputPairs)
    - kernelWeightingFunction
```
Kernel<InputType> kernelWeightingFunction
```
      Kernel function that provides the weighting for the estimate error, generally the Kernel should weight accurate estimates higher than inaccurate estimates.
    - tolerance
```
double tolerance
```
      Tolerance before stopping the algorithm
    - weightedData
```
java.util.ArrayList<E> weightedData
```
      Weighted copy of the data
- Class gov.sandia.cognition.learning.algorithm.regression.LeastSquaresEstimator extends AbstractParameterCostMinimizer<GradientDescendable,SumSquaredErrorCostFunction> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.regression.LevenbergMarquardtEstimation extends LeastSquaresEstimator implements Serializable
  - Serialized Fields
    - iterationsWithoutImprovement
```
int iterationsWithoutImprovement
```
      Number of sequential unsuccessful iterations without a cost-reducing step
    - maxIterationsWithoutImprovement
```
int maxIterationsWithoutImprovement
```
      Maximum number of iterations without improvement before stopping
    - dampingFactor
```
double dampingFactor
```
      Current damping factor for the ridge regression
    - dampingFactorDivisor
```
double dampingFactorDivisor
```
      Divisor of the damping factor on a successful iteration, must be greater then 1.0, typically ~10.0
    - bestParameters
```
Vector bestParameters
```
      Parameters used to generate the lastCost
    - bestParametersCost
```
SumSquaredErrorCostFunction.Cache bestParametersCost
```
      Cost associated with lastParameters
- Class gov.sandia.cognition.learning.algorithm.regression.LinearBasisRegression extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - inputToVectorMap
```
Evaluator<InputType,OutputType> inputToVectorMap
```
      Function that maps the InputType to a Vector
    - usePseudoInverse
```
boolean usePseudoInverse
```
      Flag to use a pseudoinverse. True to use the expensive, but more accurate, pseudoinverse routine. False uses a very fast, but numerically less stable LU solver. Default value is "true".
- Class gov.sandia.cognition.learning.algorithm.regression.LinearRegression extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - usePseudoInverse
```
boolean usePseudoInverse
```
      Flag to use a pseudoinverse. True to use the expensive, but more accurate, pseudoinverse routine. False uses a very fast, but numerically less stable LU solver. Default value is "true".
    - regularization
```
double regularization
```
      L2 ridge regularization term, must be nonnegative, a value of zero is equivalent to unregularized regression.
- Class gov.sandia.cognition.learning.algorithm.regression.LinearRegression.Statistic extends AbstractConfidenceStatistic implements Serializable
  - Serialized Fields
    - chiSquare
```
double chiSquare
```
      Gets the value of the chi-square variable, Total weighted sum-squared error between the targets and estimates
    - rootMeanSquaredError
```
double rootMeanSquaredError
```
      Root mean-squared error of the targets and estimates
    - meanL1Error
```
double meanL1Error
```
      Average L1-norm error (absolute value difference) between the targets and estimates
    - targetEstimateCorrelation
```
double targetEstimateCorrelation
```
      Pearson Correlation between the targets and estimates, [-1,1]
    - unpredictedErrorFraction
```
double unpredictedErrorFraction
```
      Fraction of variance unaccounted for in the predictions, [0,1]
    - numSamples
```
int numSamples
```
      Number of samples used to create the Regression
    - numParameters
```
int numParameters
```
      Number of parameters in the learned approximator
    - degreesOfFreedom
```
double degreesOfFreedom
```
      Degrees of freedom in the Regression = numSamples-numParameters
- Class gov.sandia.cognition.learning.algorithm.regression.LocallyWeightedFunction.Learner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - kernel
```
Kernel<InputType> kernel
```
      Kernel that provides the weights between an input and each sample in the input dataset
    - learner
```
SupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> learner
```
      Learner that takes the Collection of WeightedInputOutputPairs from the Kernel reweighting and creates a local function approximation at the given input. I would strongly recommend using fast or closed-form learners for this.
- Class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression extends AbstractAnytimeSupervisedBatchLearner<Vectorizable,java.lang.Double,LogisticRegression.Function> implements Serializable
  - Serialized Fields
    - objectToOptimize
```
LogisticRegression.Function objectToOptimize
```
      The object to optimize, used as a factory on successive runs of the algorithm.
    - result
```
LogisticRegression.Function result
```
      Return value from the algorithm
    - tolerance
```
double tolerance
```
      Tolerance change in weights before stopping
    - regularization
```
double regularization
```
      L2 ridge regularization term, must be nonnegative, a value of zero is equivalent to unregularized regression.
- Class gov.sandia.cognition.learning.algorithm.regression.LogisticRegression.Function extends CompositeEvaluatorPair<Vectorizable,java.lang.Double,java.lang.Double> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.regression.MultivariateLinearRegression extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - usePseudoInverse
```
boolean usePseudoInverse
```
      Flag to use a pseudoinverse. True to use the expensive, but more accurate, pseudoinverse routine. False uses a very fast, but numerically less stable LU solver. Default value is "true".
    - regularization
```
double regularization
```
      L2 ridge regularization term, must be nonnegative, a value of zero is equivalent to unregularized regression.
- Class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer extends AbstractMinimizerBasedParameterCostMinimizer<VectorizableVectorFunction,DifferentiableEvaluator<Vector,java.lang.Double,Vector>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.regression.ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - internalFunction
```
VectorizableVectorFunction internalFunction
```
      Object that we're tweaking the parameters of.
    - costFunction
```
SupervisedCostFunction<InputType,TargetType> costFunction
```
      Cost function against which to evaluate the cost of the object.
- Class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer extends AbstractMinimizerBasedParameterCostMinimizer<GradientDescendable,DifferentiableEvaluator<Vector,java.lang.Double,Vector>> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.regression.ParameterDifferentiableCostMinimizer.ParameterCostEvaluatorDerivativeBased extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - internalFunction
```
GradientDescendable internalFunction
```
      Object that we're tweaking the parameters of.
    - costFunction
```
DifferentiableCostFunction costFunction
```
      Cost function against which to evaluate the cost of the object.
- Class gov.sandia.cognition.learning.algorithm.regression.UnivariateLinearRegression extends AbstractCloneableSerializable implements Serializable
Package gov.sandia.cognition.learning.algorithm.root
- Class gov.sandia.cognition.learning.algorithm.root.AbstractBracketedRootFinder extends AbstractRootFinder implements Serializable
  - Serialized Fields
    - bracketer
```
RootBracketer bracketer
```
      Root-bracketing algorithm.
    - rootBracket
```
LineBracket rootBracket
```
      Gets the bracket on the root location. That is, a range of input values where a root is guaranteed to lay between.
- Class gov.sandia.cognition.learning.algorithm.root.AbstractRootFinder extends AbstractAnytimeBatchLearner<Evaluator<java.lang.Double,java.lang.Double>,InputOutputPair<java.lang.Double,java.lang.Double>> implements Serializable
  - Serialized Fields
    - tolerance
```
double tolerance
```
      Tolerance, where tolerances closer to zero are more accurate, and larger tolerances are less accurate. In any case, tolerance must be greater than or equal to zero.
    - initialGuess
```
double initialGuess
```
      Initial guess of the root location.
- Class gov.sandia.cognition.learning.algorithm.root.MinimizerBasedRootFinder extends AnytimeAlgorithmWrapper<InputOutputPair<java.lang.Double,java.lang.Double>,LineMinimizer<Evaluator<java.lang.Double,java.lang.Double>>> implements Serializable
  - Serialized Fields
    - internalFunction
```
gov.sandia.cognition.learning.algorithm.root.MinimizerBasedRootFinder.MinimizationFunction internalFunction
```
      Internal function.
- Class gov.sandia.cognition.learning.algorithm.root.RootBracketExpander extends AbstractAnytimeBatchLearner<Evaluator<java.lang.Double,java.lang.Double>,LineBracket> implements Serializable
  - Serialized Fields
    - bracket
```
LineBracket bracket
```
      Bracket on the root location.
    - initialGuess
```
double initialGuess
```
      Initial guess of the root's location.
- Class gov.sandia.cognition.learning.algorithm.root.RootFinderBisectionMethod extends AbstractBracketedRootFinder implements Serializable
- Class gov.sandia.cognition.learning.algorithm.root.RootFinderFalsePositionMethod extends AbstractBracketedRootFinder implements Serializable
- Class gov.sandia.cognition.learning.algorithm.root.RootFinderNewtonsMethod extends AbstractRootFinder implements Serializable
  - Serialized Fields
    - result
```
DefaultInputOutputPair<InputType,OutputType> result
```
      Resulting estimated location of the root.
    - dfdx
```
DifferentiableEvaluator<InputType,OutputType,DerivativeType> dfdx
```
      Internal Function variable from which we will pull the derivative. If the Evaluator is a DifferentiableEvaluator, then we will use that. Otherwise, we set up an approximation to the derivative.
    - stepMultiplier
```
double stepMultiplier
```
      Multiplier of the current step.
- Class gov.sandia.cognition.learning.algorithm.root.RootFinderRiddersMethod extends AbstractBracketedRootFinder implements Serializable
- Class gov.sandia.cognition.learning.algorithm.root.RootFinderSecantMethod extends AbstractBracketedRootFinder implements Serializable
  - Serialized Fields
    - previousPoint
```
InputOutputSlopeTriplet previousPoint
```
- Class gov.sandia.cognition.learning.algorithm.root.SolverFunction extends AbstractUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - target
```
double target
```
      internalFunction value to search for.
    - internalFunction
```
Evaluator<InputType,OutputType> internalFunction
```
      The internal function to use.
Package gov.sandia.cognition.learning.algorithm.semisupervised.valence
- Class gov.sandia.cognition.learning.algorithm.semisupervised.valence.MultipartiteValenceMatrix extends MatrixVectorMultiplier implements Serializable
  - Serialization Methods
    - readObject
```
private void readObject(java.io.ObjectInputStream ois)
                 throws java.io.IOException,
                        java.lang.ClassNotFoundException
```
      Called by de-serialization (through the magic of Java reflect) and shouldn't be called by anyone else.
      
      Throws:
      
      java.io.IOException - If there's a problem
      
      java.lang.ClassNotFoundException - If there's a problem
    - writeObject
```
private void writeObject(java.io.ObjectOutputStream oos)
                  throws java.io.IOException
```
      Called by serialization (through the magic of Java reflection) and shouldn't be called by anyone else.
      
      Throws:
      
      java.io.IOException - If there's a problem
  - Serialized Fields
    - eachPartsStart
```
int[] eachPartsStart
```
      The start position of each partition in the graph. If there are n partitions, this has length n+1 so that any single partition's size can be calculated as eachPartsStart[i+1]-eachPartsStart[i].
    - power
```
int power
```
      The power to raise the matrix to (for spreading of influence across neighbors)
    - multipartiteAdjacency
```
SparseMatrix multipartiteAdjacency
```
      The partial-solution multipartite adjacency matrix (contains all of the weighted links between partitions in a symmetric matrix).
    - additional
```
DiagonalMatrix additional
```
      The down-the-diagonal weights for solving the equation. This stores the Beta*I values from equation 5 of "Agile Sentiment..."
    - rhs
```
Vector rhs
```
      The right-hand-side vector (see equation 5)
    - isInitialized
```
boolean isInitialized
```
      True if createNormalizedLaplacian has been called more recently than addRelationship, setElementsScore, or the constructor.
    - numThreads
```
int numThreads
```
      The number of threads that this instance will use when performing matrix-vector multiplies.
Package gov.sandia.cognition.learning.algorithm.svm
- Class gov.sandia.cognition.learning.algorithm.svm.PrimalEstimatedSubGradient extends AbstractAnytimeSupervisedBatchLearner<Vectorizable,java.lang.Boolean,LinearBinaryCategorizer> implements Serializable
  - Serialized Fields
    - sampleSize
```
int sampleSize
```
      The sample size requested by the user. The actual sample size may be less than this in the case that the sample size is larger than the amount of data given in the training set.
    - regularizationWeight
```
double regularizationWeight
```
      The weight assigned to the regularization term in the algorithm, which is often represented as lambda.
    - random
```
java.util.Random random
```
      The random number generator to use.
- Class gov.sandia.cognition.learning.algorithm.svm.SequentialMinimalOptimization extends AbstractAnytimeSupervisedBatchLearner<InputType,java.lang.Boolean,KernelBinaryCategorizer<InputType,DefaultWeightedValue<InputType>>> implements Serializable
  - Serialized Fields
    - maxPenalty
```
double maxPenalty
```
      The maximum penalty parameter (C). Must be greater than 0.0.
    - errorTolerance
```
double errorTolerance
```
      The error tolerance for the algorithm. Must be non-negative. Also known as "tol" or "tolerance".
    - effectiveZero
```
double effectiveZero
```
      The effective value for zero to use in the computation to deal with numerical imprecision. Must be a non-negative number. Typically a very small value. Also sometimes known as epsilon.
    - kernelCacheSize
```
int kernelCacheSize
```
      The size of the kernel cache, which is the number of kernel computations to keep cached. May be 0 to indicate that the kernel cache should not be used.
    - random
```
java.util.Random random
```
      The random number generator to use.
    - kernel
```
Kernel<InputType> kernel
```
      The kernel to use.
- Class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation extends AbstractAnytimeSupervisedBatchLearner<InputType,java.lang.Boolean,KernelBinaryCategorizer<InputType,DefaultWeightedValue<InputType>>> implements Serializable
  - Serialized Fields
    - kernel
```
Kernel<InputType> kernel
```
      The kernel to use.
    - maxWeight
```
double maxWeight
```
      The maximum weight for a support vector. Must be greater than zero.
    - overrelaxation
```
double overrelaxation
```
      The overrelaxation parameter. Must be in (0, 2), exclusive.
    - minChange
```
double minChange
```
      The minimum change to allow for the algorithm to keep going. If the Total change is below this, then the algorithm will stop. Must be greater than zero.
    - result
```
KernelBinaryCategorizer<InputType,EntryType extends WeightedValue<? extends InputType>> result
```
      The result categorizer.
    - totalChange
```
double totalChange
```
      The total change on the most recent pass.
    - entries
```
java.util.ArrayList<E> entries
```
      The entry information that the algorithm keeps.
    - supportsMap
```
java.util.LinkedHashMap<K,V> supportsMap
```
      The mapping of weight objects to non-zero weighted examples (support vectors).
- Class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation.Entry extends DefaultWeightedValue<InputType> implements Serializable
  - Serialized Fields
    - example
```
InputOutputPair<InputType,OutputType> example
```
      The example the data pertains to.
    - output
```
boolean output
```
      The output represented as a raw boolean, to enforce that the label exists.
    - outputDouble
```
double outputDouble
```
      The output converted to a double form (+1.0 or -1.0).
    - supportInserted
```
boolean supportInserted
```
      Indicates if the support vector has been inserted into the map of support vectors or not. This allows us to keep the supports map to only contain the entries whose weights are non-zero.
    - selfKernel
```
double selfKernel
```
      This is the value of the kernel applied to the example and itself. We use this value in the update step, so we can cache it for a performance boost.
    - previousStepWeight
```
double previousStepWeight
```
      The weight of the entry on the previous step. This is used at the end of the step to calculate the total change of weights in the step.
Package gov.sandia.cognition.learning.algorithm.tree
- Class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeLearner extends AbstractIterativeAlgorithm implements Serializable
  - Serialized Fields
    - deciderLearner
```
DeciderLearner<InputType,OutputType,CategoryType,DeciderType extends Categorizer<? super InputType,? extends CategoryType>> deciderLearner
```
      The learning algorithm for the decision function.
- Class gov.sandia.cognition.learning.algorithm.tree.AbstractDecisionTreeNode extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - parent
```
DecisionTreeNode<InputType,OutputType> parent
```
      The parent node of this node.
    - childMap
```
java.util.Map<K,V> childMap
```
      The mapping of decider decision values to child nodes. For a leaf node, this can be null or empty.
    - decider
```
Categorizer<InputType,CategoryType> decider
```
      The decider used to make a decision as to which child use. For a leaf node, the decider should be null.
    - incomingValue
```
java.lang.Object incomingValue
```
      The incoming value for the node. Usually if this is null it means that the node is a root node.
- Class gov.sandia.cognition.learning.algorithm.tree.AbstractVectorThresholdMaximumGainLearner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - minSplitSize
```
int minSplitSize
```
      The threshold for allowing a split to be made, determined by how many instances fall in each left or right sides of the split. Both sides must have at least this number of instances. Must be positive.
    - dimensionsToConsider
```
int[] dimensionsToConsider
```
      The array of dimensions for the learner to consider. If this is null, then all dimensions are considered.
- Class gov.sandia.cognition.learning.algorithm.tree.CategorizationTree extends DecisionTree<InputType,OutputType> implements Serializable
  - Serialized Fields
    - categories
```
java.util.Set<E> categories
```
      The list of possible output categories.
- Class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeLearner extends AbstractDecisionTreeLearner<InputType,OutputType> implements Serializable
  - Serialized Fields
    - leafCountThreshold
```
int leafCountThreshold
```
      The threshold for making a node a leaf, determined by how many instances fall in the threshold.
    - maxDepth
```
int maxDepth
```
      The maximum depth for the tree. Ignored if less than 1.
    - priors
```
java.util.Map<K,V> priors
```
      Prior probabilities for the different categories. If null, the priors default to the category frequencies of the training data.
- Class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeNode extends AbstractDecisionTreeNode<InputType,OutputType,InteriorType> implements Serializable
  - Serialized Fields
    - outputCategory
```
java.lang.Object outputCategory
```
      The output category of the node. All nodes should have this, but it is absolutely required for a leaf node.
- Class gov.sandia.cognition.learning.algorithm.tree.DecisionTree extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - rootNode
```
DecisionTreeNode<InputType,OutputType> rootNode
```
      The root node of the decision tree.
- Class gov.sandia.cognition.learning.algorithm.tree.RandomForestFactory extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.algorithm.tree.RandomSubVectorThresholdLearner extends AbstractRandomized implements Serializable
  - Serialized Fields
    - subLearner
```
DeciderLearner<InputType,OutputType,CategoryType,DeciderType extends Categorizer<? super InputType,? extends CategoryType>> subLearner
```
      The decider learner for the subspace.
    - percentToSample
```
double percentToSample
```
      The percentage of the dimensionality to sample.
    - dimensionsToConsider
```
int[] dimensionsToConsider
```
      The dimensions to sample from in the learner.
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The vector factory to use.
- Class gov.sandia.cognition.learning.algorithm.tree.RegressionTree extends DecisionTree<InputType,java.lang.Double> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeLearner extends AbstractDecisionTreeLearner<InputType,java.lang.Double> implements Serializable
  - Serialized Fields
    - regressionLearner
```
BatchLearner<DataType,ResultType> regressionLearner
```
      The learning algorithm for the regression function.
    - leafCountThreshold
```
int leafCountThreshold
```
      The threshold for making a node a leaf, determined by how many instances fall in the threshold.
    - maxDepth
```
int maxDepth
```
      The maximum depth for the tree. Ignored if less than 1.
- Class gov.sandia.cognition.learning.algorithm.tree.RegressionTreeNode extends AbstractDecisionTreeNode<InputType,java.lang.Double,InteriorType> implements Serializable
  - Serialized Fields
    - scalarFunction
```
Evaluator<InputType,OutputType> scalarFunction
```
      The function to apply for leaf nodes.
    - value
```
double value
```
      The value stored at the tree node. It is used as a backup value if no scalar function exists for the node but the output is requested.
- Class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdGiniImpurityLearner extends AbstractVectorThresholdMaximumGainLearner<OutputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdHellingerDistanceLearner extends AbstractVectorThresholdMaximumGainLearner<OutputType> implements Serializable
- Class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdInformationGainLearner extends AbstractVectorThresholdMaximumGainLearner<OutputType> implements Serializable
  - Serialized Fields
    - categories
```
java.util.ArrayList<E> categories
```
      The categories for the prior.
    - categoryPriors
```
double[] categoryPriors
```
      The priors for each category.
    - categoryCounts
```
int[] categoryCounts
```
      The counts for each category.
    - categoryProbabilities
```
double[] categoryProbabilities
```
      Following is scratch space used when computing weighted entropy. It is declared here so it can be allocated once, instead of during every entropy evaluation.
- Class gov.sandia.cognition.learning.algorithm.tree.VectorThresholdVarianceLearner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - minSplitSize
```
int minSplitSize
```
      The threshold for allowing a split to be made, determined by how many instances fall in each left or right sides of the split. Both sides must have at least this number of instances. Must be positive.
    - dimensionsToConsider
```
int[] dimensionsToConsider
```
      The array of 0-based dimensions to consider in the input. Null means all dimensions are considered.
Package gov.sandia.cognition.learning.data
- Class gov.sandia.cognition.learning.data.AbstractInputOutputPair extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.data.AbstractTargetEstimatePair extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.data.AbstractValueDiscriminantPair extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.data.DefaultInputOutputPair extends AbstractInputOutputPair<InputType,OutputType> implements Serializable
  - Serialized Fields
    - input
```
java.lang.Object input
```
      The input.
    - output
```
java.lang.Object output
```
      The output associated with the input.
- Class gov.sandia.cognition.learning.data.DefaultTargetEstimatePair extends AbstractTargetEstimatePair<TargetType,EstimateType> implements Serializable
  - Serialized Fields
    - target
```
java.lang.Object target
```
      Target (ground-truth) value.
    - estimate
```
java.lang.Object estimate
```
      Estimate (prediction) of the target value.
- Class gov.sandia.cognition.learning.data.DefaultValueDiscriminantPair extends AbstractValueDiscriminantPair<ValueType,DiscriminantType extends java.lang.Comparable<? super DiscriminantType>> implements Serializable
  - Serialized Fields
    - value
```
java.lang.Object value
```
      The value.
    - discriminant
```
java.lang.Comparable<T> discriminant
```
      The discriminant.
- Class gov.sandia.cognition.learning.data.DefaultWeightedInputOutputPair extends DefaultInputOutputPair<InputType,OutputType> implements Serializable
  - Serialized Fields
    - weight
```
double weight
```
      Weighting term for the InputOutputPair.
- Class gov.sandia.cognition.learning.data.DefaultWeightedTargetEstimatePair extends DefaultTargetEstimatePair<TargetType,EstimateType> implements Serializable
  - Serialized Fields
    - weight
```
double weight
```
      The weight.
- Class gov.sandia.cognition.learning.data.DefaultWeightedValueDiscriminant extends DefaultWeightedValue<ValueType> implements Serializable
- Class gov.sandia.cognition.learning.data.RandomDataPartitioner extends AbstractRandomized implements Serializable
  - Serialized Fields
    - trainingPercent
```
double trainingPercent
```
      The percentage of training data.
Package gov.sandia.cognition.learning.data.feature
- Class gov.sandia.cognition.learning.data.feature.DelayFunction extends AbstractStatefulEvaluator<DataType,DataType,FiniteCapacityBuffer<DataType>> implements Serializable
  - Serialized Fields
    - delaySamples
```
int delaySamples
```
      Number of samples to delay the value
- Class gov.sandia.cognition.learning.data.feature.FeatureHashing extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - outputDimensionality
```
int outputDimensionality
```
      The output size of the hash.
    - hashFunction
```
HashFunction hashFunction
```
      The hashing function to use.
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      Vector factory to use.
- Class gov.sandia.cognition.learning.data.feature.LinearRegressionCoefficientExtractor extends AbstractStatefulEvaluator<Vector,Vector,FiniteCapacityBuffer<Vector>> implements Serializable
  - Serialized Fields
    - maxBufferSize
```
int maxBufferSize
```
      maximum number of vectors to hold in the buffer
- Class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - gaussian
```
MultivariateGaussian gaussian
```
      The underlying Gaussian.
    - covarianceInverseSquareRoot
```
Matrix covarianceInverseSquareRoot
```
      The square root of the inverse of the covariance.
- Class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.DiagonalCovarianceLearner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - defaultCovariance
```
double defaultCovariance
```
      The default covariance. Added to the diagonal to prevent it from becoming singular.
- Class gov.sandia.cognition.learning.data.feature.MultivariateDecorrelator.FullCovarianceLearner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - defaultCovariance
```
double defaultCovariance
```
      The default covariance. Added to the diagonal to prevent it from becoming singular.
- Class gov.sandia.cognition.learning.data.feature.RandomSubspace extends AbstractRandomized implements Serializable
  - Serialized Fields
    - size
```
int size
```
      The size of the random subspace to create, which is the number of dimensions that are chosen.
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The vector factory for the sub vector evaluator to use.
- Class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer extends AbstractUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - mean
```
double mean
```
      The mean of normalization.
    - variance
```
double variance
```
      The variance for normalization.
    - standardDeviation
```
double standardDeviation
```
      The cached value of the standard deviation for normalization.
- Class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer.Learner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - outlierPercent
```
double outlierPercent
```
      The percentage of outliers to exclude from learning.
Package gov.sandia.cognition.learning.experiment
- Class gov.sandia.cognition.learning.experiment.AbstractLearningExperiment extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.experiment.AbstractValidationFoldExperiment extends AbstractLearningExperiment implements Serializable
  - Serialized Fields
    - foldCreator
```
ValidationFoldCreator<InputDataType,FoldDataType> foldCreator
```
      The method to use to create the validation folds.
    - numTrials
```
int numTrials
```
      The number of trials in the experiment, which is the number of folds in the experiment.
- Class gov.sandia.cognition.learning.experiment.CrossFoldCreator extends AbstractRandomized implements Serializable
  - Serialized Fields
    - numFolds
```
int numFolds
```
      The number of folds to create.
- Class gov.sandia.cognition.learning.experiment.LearnerComparisonExperiment extends AbstractValidationFoldExperiment<InputDataType,FoldDataType> implements Serializable
  - Serialized Fields
    - performanceEvaluator
```
PerformanceEvaluator<ObjectType,DataType,ResultType> performanceEvaluator
```
      The evaluator to use to compute the performance of the learned object on each fold.
    - summarizer
```
Summarizer<DataType,SummaryType> summarizer
```
      The summarizer for summarizing the result of the performance evaluator from all the folds.
    - statisticalTest
```
NullHypothesisEvaluator<DataType> statisticalTest
```
      The statistical test to use to determine if the two learners are significantly different.
    - learners
```
Pair<FirstType,SecondType> learners
```
      The learners that the experiment is being performed on.
    - statistics
```
DefaultPair<FirstType,SecondType> statistics
```
      The performance evaluations made during the experiment.
    - confidence
```
ConfidenceStatistic confidence
```
      The confidence statistic generated from the underlying performance statistics.
    - summaries
```
DefaultPair<FirstType,SecondType> summaries
```
      The summaries of performance.
- Class gov.sandia.cognition.learning.experiment.LearnerRepeatExperiment extends AbstractLearningExperiment implements Serializable
  - Serialized Fields
    - numTrials
```
int numTrials
```
      The number of trials to repeat the learning.
    - performanceEvaluator
```
PerformanceEvaluator<ObjectType,DataType,ResultType> performanceEvaluator
```
      The evaluator to use to compute the performance of the learned object on each fold.
    - summarizer
```
Summarizer<DataType,SummaryType> summarizer
```
      The summarizer for summarizing the result of the performance evaluator from all the folds.
    - learner
```
BatchLearner<DataType,ResultType> learner
```
      The learner that the experiment is run on.
    - statistics
```
java.util.ArrayList<E> statistics
```
      The performance evaluations made during the experiment.
    - summary
```
java.lang.Object summary
```
      The summary of the performance evaluations made at the end of the experiment.
- Class gov.sandia.cognition.learning.experiment.LearnerValidationExperiment extends AbstractValidationFoldExperiment<InputDataType,FoldDataType> implements Serializable
  - Serialized Fields
    - performanceEvaluator
```
PerformanceEvaluator<ObjectType,DataType,ResultType> performanceEvaluator
```
      The evaluator to use to compute the performance of the learned object on each fold.
    - summarizer
```
Summarizer<DataType,SummaryType> summarizer
```
      The summarizer for summarizing the result of the performance evaluator from all the folds.
    - learner
```
BatchLearner<DataType,ResultType> learner
```
      The learner that the experiment is run on.
    - statistics
```
java.util.ArrayList<E> statistics
```
      The performance evaluations made during the experiment.
    - summary
```
java.lang.Object summary
```
      The summary of the performance evaluations made at the end of the experiment.
- Class gov.sandia.cognition.learning.experiment.LeaveOneOutFoldCreator extends java.lang.Object implements Serializable
- Class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment extends AbstractLearningExperiment implements Serializable
  - Serialized Fields
    - performanceEvaluator
```
PerformanceEvaluator<ObjectType,DataType,ResultType> performanceEvaluator
```
      The evaluator to use to compute the performance of the learned object on each fold.
    - summarizer
```
Summarizer<DataType,SummaryType> summarizer
```
      The summarizer for summarizing the result of the performance evaluator from all the folds.
    - numTrials
```
int numTrials
```
      The number of trials in the experiment, which is the number of folds in the experiment.
    - statistics
```
java.util.ArrayList<E> statistics
```
      The performance evaluations made during the experiment.
    - summary
```
java.lang.Object summary
```
      The summary of the performance evaluations made at the end of the experiment.
- Class gov.sandia.cognition.learning.experiment.ParallelLearnerValidationExperiment extends LearnerValidationExperiment<InputDataType,FoldDataType,LearnedType,StatisticType,SummaryType> implements Serializable
- Class gov.sandia.cognition.learning.experiment.RandomByTwoFoldCreator extends AbstractRandomized implements Serializable
  - Serialized Fields
    - numSplits
```
int numSplits
```
      The number of splits. The number of folds is twice this number.
- Class gov.sandia.cognition.learning.experiment.RandomFoldCreator extends java.lang.Object implements Serializable
  - Serialized Fields
    - numFolds
```
int numFolds
```
      The number of folds to create.
    - partitioner
```
RandomizedDataPartitioner<DataType> partitioner
```
      The partitioner used for each fold.
- Class gov.sandia.cognition.learning.experiment.SupervisedLearnerComparisonExperiment extends LearnerComparisonExperiment<InputOutputPair<InputType,OutputType>,InputOutputPair<InputType,OutputType>,Evaluator<? super InputType,OutputType>,StatisticType,SummaryType> implements Serializable
- Class gov.sandia.cognition.learning.experiment.SupervisedLearnerValidationExperiment extends LearnerValidationExperiment<InputOutputPair<InputType,OutputType>,InputOutputPair<InputType,OutputType>,Evaluator<? super InputType,OutputType>,StatisticType,SummaryType> implements Serializable
Package gov.sandia.cognition.learning.function
- Class gov.sandia.cognition.learning.function.ConstantEvaluator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - value
```
java.lang.Object value
```
      The output value.
- Class gov.sandia.cognition.learning.function.LinearCombinationFunction extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - basisFunctions
```
java.util.ArrayList<E> basisFunctions
```
      Collection of basis functions to combine to produce the output
    - coefficients
```
Vector coefficients
```
      Coefficients for the basisFunctions
Package gov.sandia.cognition.learning.function.categorization
- Class gov.sandia.cognition.learning.function.categorization.AbstractBinaryCategorizer extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.function.categorization.AbstractCategorizer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - categories
```
java.util.Set<E> categories
```
      The set of categories that are the possible output values of the categorizer.
- Class gov.sandia.cognition.learning.function.categorization.AbstractConfidenceWeightedBinaryCategorizer extends LinearBinaryCategorizer implements Serializable
- Class gov.sandia.cognition.learning.function.categorization.AbstractDiscriminantBinaryCategorizer extends AbstractBinaryCategorizer<InputType> implements Serializable
- Class gov.sandia.cognition.learning.function.categorization.AbstractDiscriminantCategorizer extends AbstractCategorizer<InputType,CategoryType> implements Serializable
- Class gov.sandia.cognition.learning.function.categorization.AbstractThresholdBinaryCategorizer extends AbstractDiscriminantBinaryCategorizer<InputType> implements Serializable
  - Serialized Fields
    - threshold
```
double threshold
```
      Threshold, below which I will return lowValue, above or equal to I will return highValue.
- Class gov.sandia.cognition.learning.function.categorization.BinaryVersusCategorizer extends AbstractDiscriminantCategorizer<InputType,CategoryType,java.lang.Double> implements Serializable
  - Serialized Fields
    - categoryPairsToEvaluatorMap
```
java.util.Map<K,V> categoryPairsToEvaluatorMap
```
      Maps false-true category pairs .
- Class gov.sandia.cognition.learning.function.categorization.BinaryVersusCategorizer.Learner extends AbstractBatchLearnerContainer<BatchLearner<? super java.util.Collection<? extends InputOutputPair<? extends InputType,java.lang.Boolean>>,? extends Evaluator<? super InputType,java.lang.Boolean>>> implements Serializable
- Class gov.sandia.cognition.learning.function.categorization.CompositeCategorizer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - preprocessor
```
Evaluator<InputType,OutputType> preprocessor
```
      The preprocessor for the input data.
    - categorizer
```
Categorizer<InputType,CategoryType> categorizer
```
      The categorizer.
- Class gov.sandia.cognition.learning.function.categorization.DefaultConfidenceWeightedBinaryCategorizer extends AbstractConfidenceWeightedBinaryCategorizer implements Serializable
  - Serialized Fields
    - covariance
```
Matrix covariance
```
      The covariance matrix.
- Class gov.sandia.cognition.learning.function.categorization.DefaultKernelBinaryCategorizer extends KernelBinaryCategorizer<InputType,DefaultWeightedValue<InputType>> implements Serializable
- Class gov.sandia.cognition.learning.function.categorization.DiagonalConfidenceWeightedBinaryCategorizer extends AbstractConfidenceWeightedBinaryCategorizer implements Serializable
  - Serialized Fields
    - variance
```
Vector variance
```
      The variance values, which is the diagonal of the covariance matrix. It is stored as a vector to avoid needing to instantiate and use matrix operations with it.
- Class gov.sandia.cognition.learning.function.categorization.EvaluatorToCategorizerAdapter extends AbstractCategorizer<InputType,CategoryType> implements Serializable
  - Serialized Fields
    - evaluator
```
Evaluator<InputType,OutputType> evaluator
```
      The evaluator that is being wrapped into a categorizer.
- Class gov.sandia.cognition.learning.function.categorization.EvaluatorToCategorizerAdapter.Learner extends AbstractBatchLearnerContainer<BatchLearner<? super java.util.Collection<? extends InputOutputPair<? extends InputType,CategoryType>>,? extends Evaluator<? super InputType,? extends CategoryType>>> implements Serializable
- Class gov.sandia.cognition.learning.function.categorization.FisherLinearDiscriminantBinaryCategorizer extends ScalarFunctionToBinaryCategorizerAdapter<Vector> implements Serializable
- Class gov.sandia.cognition.learning.function.categorization.FisherLinearDiscriminantBinaryCategorizer.ClosedFormSolver extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - defaultCovariance
```
double defaultCovariance
```
      The default covariance.
- Class gov.sandia.cognition.learning.function.categorization.KernelBinaryCategorizer extends AbstractDiscriminantBinaryCategorizer<InputType> implements Serializable
  - Serialized Fields
    - kernel
```
Kernel<InputType> kernel
```
      The internal kernel.
    - examples
```
java.util.Collection<E> examples
```
      The list of weighted examples that are used for categorization.
    - bias
```
double bias
```
      The bias term.
- Class gov.sandia.cognition.learning.function.categorization.LinearBinaryCategorizer extends AbstractDiscriminantBinaryCategorizer<Vectorizable> implements Serializable
  - Serialized Fields
    - weights
```
Vector weights
```
      The weight vector.
    - bias
```
double bias
```
      The bias term.
- Class gov.sandia.cognition.learning.function.categorization.LinearMultiCategorizer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - prototypes
```
java.util.Map<K,V> prototypes
```
      A map of each category to its prototype categorizer.
- Class gov.sandia.cognition.learning.function.categorization.MaximumAPosterioriCategorizer extends AbstractDistribution<ObservationType> implements Serializable
  - Serialized Fields
    - categoryPriors
```
DataDistribution.PMF<KeyType> categoryPriors
```
      PMF of the various categories
    - categoryConditionals
```
java.util.Map<K,V> categoryConditionals
```
      Map that contains the probability functions for the observations for the given categories.
- Class gov.sandia.cognition.learning.function.categorization.MaximumAPosterioriCategorizer.Learner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - conditionalLearner
```
BatchLearner<DataType,ResultType> conditionalLearner
```
      Learner that creates the conditional distributions for each category.
- Class gov.sandia.cognition.learning.function.categorization.ScalarFunctionToBinaryCategorizerAdapter extends AbstractThresholdBinaryCategorizer<InputType> implements Serializable
  - Serialized Fields
    - evaluator
```
Evaluator<InputType,OutputType> evaluator
```
      The scalar evaluator.
- Class gov.sandia.cognition.learning.function.categorization.ScalarThresholdBinaryCategorizer extends AbstractThresholdBinaryCategorizer<java.lang.Double> implements Serializable
- Class gov.sandia.cognition.learning.function.categorization.VectorElementThresholdCategorizer extends AbstractThresholdBinaryCategorizer<Vectorizable> implements Serializable
  - Serialized Fields
    - index
```
int index
```
      The index to apply the threshold to.
- Class gov.sandia.cognition.learning.function.categorization.WinnerTakeAllCategorizer extends AbstractDiscriminantCategorizer<InputType,CategoryType,java.lang.Double> implements Serializable
  - Serialized Fields
    - evaluator
```
Evaluator<InputType,OutputType> evaluator
```
      The evaluator that outputs a vector to return.
- Class gov.sandia.cognition.learning.function.categorization.WinnerTakeAllCategorizer.Learner extends AbstractBatchLearnerContainer<BatchLearner<? super java.util.Collection<? extends InputOutputPair<? extends InputType,Vector>>,? extends Evaluator<? super InputType,? extends Vectorizable>>> implements Serializable
  - Serialized Fields
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The vector factory used.
Package gov.sandia.cognition.learning.function.cost
- Class gov.sandia.cognition.learning.function.cost.AbstractCostFunction extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - costParameters
```
java.lang.Object costParameters
```
      The parameters of the cost function.
- Class gov.sandia.cognition.learning.function.cost.AbstractParallelizableCostFunction extends AbstractSupervisedCostFunction<Vector,Vector> implements Serializable
- Class gov.sandia.cognition.learning.function.cost.AbstractSupervisedCostFunction extends AbstractSupervisedPerformanceEvaluator<InputType,TargetType,TargetType,java.lang.Double> implements Serializable
  - Serialized Fields
    - costParameters
```
java.util.Collection<E> costParameters
```
      Labeled dataset to use to evaluate the cost against
- Class gov.sandia.cognition.learning.function.cost.ClusterDistortionMeasure extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - costParameters
```
ClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> costParameters
```
      Divergence function that defines the cost function
- Class gov.sandia.cognition.learning.function.cost.EuclideanDistanceCostFunction extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - goal
```
Vector goal
```
      The goal of the cost function.
- Class gov.sandia.cognition.learning.function.cost.KolmogorovSmirnovDivergence extends AbstractCostFunction<UnivariateDistribution<DataType extends java.lang.Number>,java.util.Collection<? extends DataType extends java.lang.Number>> implements Serializable
- Class gov.sandia.cognition.learning.function.cost.MeanL1CostFunction extends AbstractSupervisedCostFunction<Vector,Vector> implements Serializable
- Class gov.sandia.cognition.learning.function.cost.MeanSquaredErrorCostFunction extends AbstractSupervisedCostFunction<Vector,Vector> implements Serializable
- Class gov.sandia.cognition.learning.function.cost.NegativeLogLikelihood extends AbstractCostFunction<ComputableDistribution<DataType>,java.util.Collection<? extends DataType>> implements Serializable
- Class gov.sandia.cognition.learning.function.cost.ParallelClusterDistortionMeasure extends ClusterDistortionMeasure<DataType,ClusterType extends Cluster<DataType>> implements Serializable
- Class gov.sandia.cognition.learning.function.cost.ParallelizedCostFunctionContainer extends AbstractSupervisedCostFunction<Vector,Vector> implements Serializable
  - Serialized Fields
    - costFunction
```
ParallelizableCostFunction costFunction
```
      Cost function to parallelize
- Class gov.sandia.cognition.learning.function.cost.ParallelNegativeLogLikelihood extends NegativeLogLikelihood<DataType> implements Serializable
- Class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction extends AbstractParallelizableCostFunction implements Serializable
- Class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction.Cache extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - J
```
Matrix J
```
      Jacobian
    - JtJ
```
Matrix JtJ
```
      Inner-product of the Jacobian matrix: J.transpose().times( J )
    - Jte
```
Vector Jte
```
      Jacobian transpose times Error: J.transpose().times( error )
    - parameterCost
```
double parameterCost
```
      Cost-function value of the parameter set
- Class gov.sandia.cognition.learning.function.cost.SumSquaredErrorCostFunction.GradientPartialSSE extends DefaultPair<Vector,java.lang.Double> implements Serializable
Package gov.sandia.cognition.learning.function.distance
- Class gov.sandia.cognition.learning.function.distance.ChebyshevDistanceMetric extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.function.distance.CosineDistanceMetric extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - divergenceFunction
```
DivergenceFunction<FirstType,SecondType> divergenceFunction
```
      The internal divergence function for the object to use.
- Class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator extends AbstractToVectorEncoder<InputType> implements Serializable
  - Serialized Fields
    - divergenceFunction
```
DivergenceFunction<FirstType,SecondType> divergenceFunction
```
      The divergence function to apply between the data and the input.
    - values
```
java.util.Collection<E> values
```
      The data to evaluate the divergence from.
- Class gov.sandia.cognition.learning.function.distance.DivergencesEvaluator.Learner extends AbstractBatchLearnerContainer<BatchLearner<? super DataType,? extends java.util.Collection<ValueType>>> implements Serializable
  - Serialized Fields
    - divergenceFunction
```
DivergenceFunction<FirstType,SecondType> divergenceFunction
```
      The divergence function to apply between the data and the input.
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The vector factory to use.
- Class gov.sandia.cognition.learning.function.distance.EuclideanDistanceMetric extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.function.distance.EuclideanDistanceSquaredMetric extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.function.distance.IdentityDistanceMetric extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.function.distance.ManhattanDistanceMetric extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.function.distance.MinkowskiDistanceMetric extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - power
```
double power
```
      The power that the distance is computed to.
- Class gov.sandia.cognition.learning.function.distance.WeightedEuclideanDistanceMetric extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - weights
```
Vector weights
```
      The weights assigned to each dimension for the distance. The weights cannot be negative.
Package gov.sandia.cognition.learning.function.kernel
- Class gov.sandia.cognition.learning.function.kernel.DefaultKernelContainer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - kernel
```
Kernel<InputType> kernel
```
      The internal kernel.
- Class gov.sandia.cognition.learning.function.kernel.DefaultKernelsContainer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - kernels
```
java.util.Collection<E> kernels
```
      The collection of kernels in the container.
- Class gov.sandia.cognition.learning.function.kernel.ExponentialKernel extends DefaultKernelContainer<InputType> implements Serializable
- Class gov.sandia.cognition.learning.function.kernel.KernelDistanceMetric extends DefaultKernelContainer<InputType> implements Serializable
- Class gov.sandia.cognition.learning.function.kernel.LinearKernel extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.function.kernel.NormalizedKernel extends DefaultKernelContainer<InputType> implements Serializable
- Class gov.sandia.cognition.learning.function.kernel.PolynomialKernel extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - degree
```
int degree
```
      The degree of the polynomial. Must be positive.
    - constant
```
double constant
```
      The constant for the polynomial.
- Class gov.sandia.cognition.learning.function.kernel.ProductKernel extends DefaultKernelsContainer<InputType> implements Serializable
- Class gov.sandia.cognition.learning.function.kernel.RadialBasisKernel extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - sigma
```
double sigma
```
      Sigma is the parameter that controls the bandwidth of the radial basis kernel.
    - negativeTwoSigmaSquared
```
double negativeTwoSigmaSquared
```
      This value is cached so it doesn't have to be computed each time. It is -2.0 * sigma * sigma.
- Class gov.sandia.cognition.learning.function.kernel.ScalarFunctionKernel extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - function
```
Evaluator<InputType,OutputType> function
```
      The scalar function for the kernel to use.
- Class gov.sandia.cognition.learning.function.kernel.SigmoidKernel extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - kappa
```
double kappa
```
      The kappa value to multiply times the dot product.
    - constant
```
double constant
```
      The constant used in the sigmoid.
- Class gov.sandia.cognition.learning.function.kernel.SumKernel extends DefaultKernelsContainer<InputType> implements Serializable
- Class gov.sandia.cognition.learning.function.kernel.VectorFunctionKernel extends DefaultKernelContainer<Vector> implements Serializable
  - Serialized Fields
    - function
```
VectorFunction function
```
      The vector function to use.
- Class gov.sandia.cognition.learning.function.kernel.WeightedKernel extends DefaultKernelContainer<InputType> implements Serializable
  - Serialized Fields
    - weight
```
double weight
```
      The weight on the kernel. Must be non-negative.
- Class gov.sandia.cognition.learning.function.kernel.ZeroKernel extends AbstractCloneableSerializable implements Serializable
Package gov.sandia.cognition.learning.function.regression
- Class gov.sandia.cognition.learning.function.regression.AbstractRegressor extends AbstractScalarFunction<InputType> implements Serializable
Package gov.sandia.cognition.learning.function.scalar
- Class gov.sandia.cognition.learning.function.scalar.AtanFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - scaleFactor
```
double scaleFactor
```
      Scales the Math.atan() value to ensure that it has the desired "maxMagnitude"
- Class gov.sandia.cognition.learning.function.scalar.CosineFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - amplitude
```
double amplitude
```
      Maximum value of the cosine function. The value of "A" in y=A*cos(2*pi*f*x + phase).
    - frequency
```
double frequency
```
      Frequency of the cosine function. The value of "f" in y=A*cos(2*pi*f*x + phase).
    - phase
```
double phase
```
      Phase of the cosine function. The value of "phase" in y=A*cos(2*pi*f*x + phase).
- Class gov.sandia.cognition.learning.function.scalar.HardSigmoidFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
- Class gov.sandia.cognition.learning.function.scalar.HardTanHFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
- Class gov.sandia.cognition.learning.function.scalar.IdentityScalarFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
- Class gov.sandia.cognition.learning.function.scalar.KernelScalarFunction extends DefaultKernelContainer<InputType> implements Serializable
  - Serialized Fields
    - examples
```
java.util.Collection<E> examples
```
      The list of weighted examples that are used for categorization.
    - bias
```
double bias
```
      The bias term.
- Class gov.sandia.cognition.learning.function.scalar.KolmogorovSmirnovEvaluator extends AbstractStatefulEvaluator<java.lang.Double,java.lang.Double,FiniteCapacityBuffer<java.lang.Double>> implements Serializable
  - Serialized Fields
    - cdf
```
CumulativeDistributionFunction<NumberType extends java.lang.Number> cdf
```
      The cumulative distribution function to base the evaluator on.
    - capacity
```
int capacity
```
      The capacity of the state.
- Class gov.sandia.cognition.learning.function.scalar.LeakyRectifiedLinearFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - leakage
```
double leakage
```
      The amount of leakage for when the value is less than zero.
- Class gov.sandia.cognition.learning.function.scalar.LinearCombinationScalarFunction extends LinearCombinationFunction<InputType,java.lang.Double> implements Serializable
- Class gov.sandia.cognition.learning.function.scalar.LinearDiscriminant extends AbstractRegressor<Vectorizable> implements Serializable
  - Serialized Fields
    - weightVector
```
Vector weightVector
```
      Weight Vector to dot-product with the input
- Class gov.sandia.cognition.learning.function.scalar.LinearDiscriminantWithBias extends LinearDiscriminant implements Serializable
  - Serialized Fields
    - bias
```
double bias
```
      Bias term that gets added to the output of the dot product.
- Class gov.sandia.cognition.learning.function.scalar.LinearFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - slope
```
double slope
```
      The slope (m).
    - offset
```
double offset
```
      The offset (b).
- Class gov.sandia.cognition.learning.function.scalar.LinearVectorScalarFunction extends AbstractRegressor<Vectorizable> implements Serializable
  - Serialized Fields
    - weights
```
Vector weights
```
      The weight vector.
    - bias
```
double bias
```
      The bias term.
- Class gov.sandia.cognition.learning.function.scalar.LocallyWeightedKernelScalarFunction extends KernelScalarFunction<InputType> implements Serializable
  - Serialized Fields
    - constantWeight
```
double constantWeight
```
      The constant weight is used as a weight for the constant value that is added to the result to bias the function to the constant value.
    - constantValue
```
double constantValue
```
      The constant value is what the constant weight biases the function toward when there is near zero weight.
- Class gov.sandia.cognition.learning.function.scalar.PolynomialFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - exponent
```
double exponent
```
      Real-valued exponent of this polynomial
- Class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Cubic extends PolynomialFunction.Quadratic implements Serializable
  - Serialized Fields
    - q3
```
double q3
```
      Cubic (third-order) coefficient
- Class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Linear extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - q0
```
double q0
```
      Constant (zeroth-order) coefficient
    - q1
```
double q1
```
      Linear (first-order) coefficient
- Class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Quadratic extends PolynomialFunction.Linear implements Serializable
  - Serialized Fields
    - q2
```
double q2
```
      Quadratic (second-order) coefficient
- Class gov.sandia.cognition.learning.function.scalar.PolynomialFunction.Regression extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - polynomials
```
ScalarBasisSet<InputType> polynomials
```
      Polynomials to use in the regression
- Class gov.sandia.cognition.learning.function.scalar.RectifiedLinearFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
- Class gov.sandia.cognition.learning.function.scalar.SigmoidFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
- Class gov.sandia.cognition.learning.function.scalar.SoftPlusFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
- Class gov.sandia.cognition.learning.function.scalar.TanHFunction extends AbstractDifferentiableUnivariateScalarFunction implements Serializable
- Class gov.sandia.cognition.learning.function.scalar.ThresholdFunction extends AbstractUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - highValue
```
double highValue
```
      Values above (or equal to) threshold are assigned this value
    - lowValue
```
double lowValue
```
      Values below threshold are assigned this value
    - threshold
```
double threshold
```
      Current threshold, below which a value is assigned lowValue, above which (or equal to) is assigned highValue
- Class gov.sandia.cognition.learning.function.scalar.VectorEntryFunction extends AbstractScalarFunction<Vectorizable> implements Serializable
  - Serialized Fields
    - index
```
int index
```
      The index of the vector to get.
- Class gov.sandia.cognition.learning.function.scalar.VectorFunctionLinearDiscriminant extends AbstractRegressor<InputType> implements Serializable
  - Serialized Fields
    - vectorFunction
```
Evaluator<InputType,OutputType> vectorFunction
```
      Maps the input space to a Vector
    - discriminant
```
LinearDiscriminant discriminant
```
      The dot product of the discriminant with the output of the vectorFunction is the output (scalar) value. Must have the same dimensions as the outputDimensionality of vectorFunction.
- Class gov.sandia.cognition.learning.function.scalar.VectorFunctionToScalarFunction extends AbstractRegressor<InputType> implements Serializable
  - Serialized Fields
    - vectorFunction
```
Evaluator<InputType,OutputType> vectorFunction
```
      The function that takes a given input and outputs a 1-dimensional vector.
- Class gov.sandia.cognition.learning.function.scalar.VectorFunctionToScalarFunction.Learner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - vectorLearner
```
BatchLearner<DataType,ResultType> vectorLearner
```
      The supervised learner that learns on vectors as outputs.
Package gov.sandia.cognition.learning.function.summarizer
- Class gov.sandia.cognition.learning.function.summarizer.MostFrequentSummarizer extends AbstractCloneableSerializable implements Serializable
Package gov.sandia.cognition.learning.function.vector
- Class gov.sandia.cognition.learning.function.vector.DifferentiableFeedforwardNeuralNetwork extends FeedforwardNeuralNetwork implements Serializable
- Class gov.sandia.cognition.learning.function.vector.DifferentiableGeneralizedLinearModel extends GeneralizedLinearModel implements Serializable
- Class gov.sandia.cognition.learning.function.vector.ElementWiseDifferentiableVectorFunction extends ElementWiseVectorFunction implements Serializable
- Class gov.sandia.cognition.learning.function.vector.ElementWiseVectorFunction extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - scalarFunction
```
UnivariateScalarFunction scalarFunction
```
      Underlying scalar function to apply to each Vector element
- Class gov.sandia.cognition.learning.function.vector.EntropyEvaluator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.function.vector.FeedforwardNeuralNetwork extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - layers
```
java.util.ArrayList<E> layers
```
      Layers that comprise this neural network
- Class gov.sandia.cognition.learning.function.vector.GaussianContextRecognizer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - gaussianMixture
```
MixtureOfGaussians.PDF gaussianMixture
```
      Underlying MixtureOfGaussians that computes context probabilities
- Class gov.sandia.cognition.learning.function.vector.GaussianContextRecognizer.Learner extends AnytimeAlgorithmWrapper<GaussianContextRecognizer,AnytimeBatchLearner<java.util.Collection<? extends Vector>,java.util.Collection<GaussianCluster>>> implements Serializable
- Class gov.sandia.cognition.learning.function.vector.GeneralizedLinearModel extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - discriminant
```
MultivariateDiscriminant discriminant
```
      GradientDescendable that multiplies an input by the internal matrix
    - squashingFunction
```
VectorFunction squashingFunction
```
      VectorFunction that is applied to the output of the matrix multiply
- Class gov.sandia.cognition.learning.function.vector.LinearCombinationVectorFunction extends LinearCombinationFunction<Vector,Vector> implements Serializable
- Class gov.sandia.cognition.learning.function.vector.LinearVectorFunction extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - scaleFactor
```
double scaleFactor
```
      Scales the input by this amount.
- Class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminant extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - discriminant
```
Matrix discriminant
```
      Internal matrix to premultiply input vectors by.
- Class gov.sandia.cognition.learning.function.vector.MultivariateDiscriminantWithBias extends MultivariateDiscriminant implements Serializable
  - Serialized Fields
    - bias
```
Vector bias
```
      Bias term that gets added the output of the matrix multiplication.
- Class gov.sandia.cognition.learning.function.vector.ScalarBasisSet extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - basisFunctions
```
java.util.Collection<E> basisFunctions
```
      Collection of scalar basis functions, where the ith function operates on the ith element of the output Vector
- Class gov.sandia.cognition.learning.function.vector.SubVectorEvaluator extends DefaultVectorFactoryContainer implements Serializable
  - Serialized Fields
    - inputDimensionality
```
int inputDimensionality
```
      The expected dimensionality of the input. All the subIndices must be less than this value.
    - subIndices
```
int[] subIndices
```
      The indices to pull out of an input vector to create a new vector from.
- Class gov.sandia.cognition.learning.function.vector.ThreeLayerFeedforwardNeuralNetwork extends AbstractRandomized implements Serializable
  - Serialized Fields
    - inputToHiddenWeights
```
Matrix inputToHiddenWeights
```
      Matrix of weights to pre-multiply the inputs by.
    - inputToHiddenBiasWeights
```
Vector inputToHiddenBiasWeights
```
      Bias weights to add to each of the hidden units.
    - hiddenToOutputWeights
```
Matrix hiddenToOutputWeights
```
      Matrix of weights to pre-multiply the hidden-unit activations by.
    - hiddenToOutputBiasWeights
```
Vector hiddenToOutputBiasWeights
```
      Bias weights to add to each of the output units.
    - squashingFunction
```
DifferentiableUnivariateScalarFunction squashingFunction
```
      Squashing function to apply at the hidden layer.
    - initializationRange
```
double initializationRange
```
      Range of values to initialize the weights between, must be greater than or equal to zero.
- Class gov.sandia.cognition.learning.function.vector.VectorizableVectorConverter extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.function.vector.VectorizableVectorConverterWithBias extends VectorizableVectorConverter implements Serializable
  - Serialized Fields
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The factory used to create the vector.
Package gov.sandia.cognition.learning.parameter
- Class gov.sandia.cognition.learning.parameter.ParameterAdaptableBatchLearnerWrapper extends AbstractBatchLearnerContainer<LearnerType extends BatchLearner<? super DataType,? extends ResultType>> implements Serializable
  - Serialized Fields
    - parameterAdapters
```
java.util.LinkedList<E> parameterAdapters
```
      The list of parameter adapters for the learner. It should be null if there are no adapters.
Package gov.sandia.cognition.learning.performance
- Class gov.sandia.cognition.learning.performance.AbstractSupervisedPerformanceEvaluator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.performance.AnytimeBatchLearnerValidationPerformanceReporter extends AbstractIterativeAlgorithmListener implements Serializable
  - Serialized Fields
    - performanceEvaluator
```
PerformanceEvaluator<ObjectType,DataType,ResultType> performanceEvaluator
```
      The performance evaluator. Produces the metrics.
    - validationData
```
java.lang.Object validationData
```
      The validation dataset to use.
    - out
```
java.io.PrintStream out
```
      The print stream to report performance to.
    - format
```
java.lang.String format
```
      The format for the performance report, passed to String.format.
- Class gov.sandia.cognition.learning.performance.MeanAbsoluteErrorEvaluator extends AbstractSupervisedPerformanceEvaluator<InputType,java.lang.Double,java.lang.Double,java.lang.Double> implements Serializable
- Class gov.sandia.cognition.learning.performance.MeanSquaredErrorEvaluator extends AbstractSupervisedPerformanceEvaluator<InputType,java.lang.Double,java.lang.Double,java.lang.Double> implements Serializable
- Class gov.sandia.cognition.learning.performance.MeanZeroOneErrorEvaluator extends AbstractSupervisedCostFunction<InputType,DataType> implements Serializable
- Class gov.sandia.cognition.learning.performance.RootMeanSquaredErrorEvaluator extends AbstractSupervisedPerformanceEvaluator<InputType,java.lang.Double,java.lang.Double,java.lang.Double> implements Serializable
Package gov.sandia.cognition.learning.performance.categorization
- Class gov.sandia.cognition.learning.performance.categorization.AbstractBinaryConfusionMatrix extends AbstractConfusionMatrix<java.lang.Boolean> implements Serializable
- Class gov.sandia.cognition.learning.performance.categorization.AbstractConfusionMatrix extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.performance.categorization.ConfusionMatrixPerformanceEvaluator extends AbstractSupervisedPerformanceEvaluator<InputType,CategoryType,CategoryType,ConfusionMatrix<CategoryType>> implements Serializable
  - Serialized Fields
    - factory
```
Factory<CreatedType> factory
```
      The factory used to create the confusion matrix of the evaluator.
- Class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix extends AbstractBinaryConfusionMatrix implements Serializable
  - Serialized Fields
    - trueNegativesCount
```
double trueNegativesCount
```
      Number of true negatives. The (false, false) entry.
    - falsePositivesCount
```
double falsePositivesCount
```
      Number of false positives. The (false, true) entry.
    - falseNegativesCount
```
double falseNegativesCount
```
      Number of false negatives. The (true, false) entry.
    - truePositivesCount
```
double truePositivesCount
```
      Number of true positives. The (true, true) entry.
- Class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix.ActualPredictedPairSummarizer extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix.CombineSummarizer extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrix.PerformanceEvaluator extends AbstractSupervisedPerformanceEvaluator<InputType,java.lang.Boolean,java.lang.Boolean,DefaultBinaryConfusionMatrix> implements Serializable
- Class gov.sandia.cognition.learning.performance.categorization.DefaultBinaryConfusionMatrixConfidenceInterval.Summary extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - confidence
```
double confidence
```
      The confidence for the created interval.
- Class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix extends AbstractConfusionMatrix<CategoryType> implements Serializable
  - Serialized Fields
    - confusions
```
java.util.Map<K,V> confusions
```
      The backing map of confusion matrix entries. The first key is the actual category and the second is the predicted category.
- Class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix.ActualPredictedPairSummarizer extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix.CombineSummarizer extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.learning.performance.categorization.DefaultConfusionMatrix.Factory extends AbstractCloneableSerializable implements Serializable
Package gov.sandia.cognition.math
- Class gov.sandia.cognition.math.AbstractDifferentiableUnivariateScalarFunction extends AbstractUnivariateScalarFunction implements Serializable
- Class gov.sandia.cognition.math.AbstractEuclideanRing extends AbstractRing<RingType extends EuclideanRing<RingType>> implements Serializable
- Class gov.sandia.cognition.math.AbstractField extends AbstractEuclideanRing<FieldType extends Field<FieldType>> implements Serializable
- Class gov.sandia.cognition.math.AbstractRing extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.math.AbstractScalarFunction extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.math.AbstractUnivariateScalarFunction extends AbstractScalarFunction<java.lang.Double> implements Serializable
- Class gov.sandia.cognition.math.Combinations extends java.util.AbstractSet<Vector> implements Serializable
  - Serialized Fields
    - N
```
int N
```
      Universe set size
    - k
```
int k
```
      Number of objects to choose from the universe set.
- Class gov.sandia.cognition.math.Combinations.AbstractCombinationsIterator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - N
```
int N
```
      Universe set size
    - k
```
int k
```
      Number of objects to choose from the universe set.
    - size
```
int size
```
    - index
```
int index
```
      Index into the universal set.
    - child
```
Combinations.AbstractCombinationsIterator<IteratorType extends Combinations.AbstractCombinationsIterator<IteratorType,ClassType>,ClassType> child
```
      Child iterator for recursion
- Class gov.sandia.cognition.math.Combinations.IndexIterator extends Combinations.AbstractCombinationsIterator<Combinations.IndexIterator,Vector> implements Serializable
  - Serialized Fields
    - value
```
double value
```
      Value to return
- Class gov.sandia.cognition.math.Combinations.SubsetIterator extends Combinations.AbstractCombinationsIterator<Combinations.SubsetIterator<ClassType>,java.util.LinkedList<ClassType>> implements Serializable
  - Serialized Fields
    - set
```
java.util.ArrayList<E> set
```
      Universal set into which to index.
    - include
```
boolean include
```
      Flag to include the current element
    - baseIndex
```
int baseIndex
```
      Base index into the universal set from which we recursed
- Class gov.sandia.cognition.math.ComplexNumber extends AbstractField<ComplexNumber> implements Serializable
  - Serialized Fields
    - realPart
```
double realPart
```
      The real part of the ComplexNumber
    - imaginaryPart
```
double imaginaryPart
```
      The imaginary part of the ComplexNumber
- Class gov.sandia.cognition.math.LentzMethod extends AbstractAnytimeAlgorithm<java.lang.Double> implements Serializable
  - Serialized Fields
    - tolerance
```
double tolerance
```
      Tolerance of the algorithm for convergence
    - minDenominator
```
double minDenominator
```
      Value to keep denominators from equaling 0.0
    - currentC
```
double currentC
```
      Current value of the "C" variable in Lentz's method
    - currentD
```
double currentD
```
      Current value of the "D" variable in Lentz's method
    - result
```
java.lang.Double result
```
      Value of the continued fraction, null if not valid
    - fractionValue
```
double fractionValue
```
      Running (intermediate) value of the fraction value
    - keepGoing
```
boolean keepGoing
```
      Flag to keep going or stop
- Class gov.sandia.cognition.math.LogNumber extends java.lang.Number implements Serializable
  - Serialized Fields
    - negative
```
boolean negative
```
      The sign of the value, sign(value). True for negative, and false for positive.
    - logValue
```
double logValue
```
      The log of the absolute value represented by this object, log(|value|).
- Class gov.sandia.cognition.math.MutableDouble extends java.lang.Number implements Serializable
  
  serialVersionUID:
  
  20110131L
  - Serialized Fields
    - value
```
double value
```
      The value. Note: This is public just for performance reasons when people don't want to do the getter/setter for overhead reasons.
- Class gov.sandia.cognition.math.MutableInteger extends java.lang.Number implements Serializable
  
  serialVersionUID:
  
  20110601L
  - Serialized Fields
    - value
```
int value
```
      The value. Note: This is public just for performance reasons when people don't want to do the getter/setter for overhead reasons.
- Class gov.sandia.cognition.math.MutableLong extends java.lang.Number implements Serializable
  
  serialVersionUID:
  
  20110602L
  - Serialized Fields
    - value
```
long value
```
      The value. Note: This is public just for performance reasons when people don't want to do the getter/setter for overhead reasons.
- Class gov.sandia.cognition.math.NumberAverager extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.math.OperationNotConvergedException extends java.lang.RuntimeException implements Serializable
- Class gov.sandia.cognition.math.RingAverager extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.math.UnivariateSummaryStatistics extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - min
```
double min
```
      Min
    - max
```
double max
```
      Max
    - quintiles
```
double[] quintiles
```
      Quintile boundaries
    - confidenceLower
```
double confidenceLower
```
      Lower 95% confidence region (alpha=0.025)
    - confidenceUpper
```
double confidenceUpper
```
      Upper 95% confidence region (alpha=0.975)
    - median
```
double median
```
      Median
    - numSamples
```
int numSamples
```
      Number of samples
    - mean
```
double mean
```
      Arithmetic mean
    - variance
```
double variance
```
      Variance
    - skewness
```
double skewness
```
      Skew
    - kurtosis
```
double kurtosis
```
      Excess kurtosis
- Class gov.sandia.cognition.math.UnsignedLogNumber extends java.lang.Number implements Serializable
  - Serialized Fields
    - logValue
```
double logValue
```
      The log of the value represented by this object, log(value).
- Class gov.sandia.cognition.math.WeightedNumberAverager extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.math.WeightedRingAverager extends AbstractCloneableSerializable implements Serializable
Package gov.sandia.cognition.math.geometry
- Class gov.sandia.cognition.math.geometry.KDTree extends java.util.AbstractCollection<PairType extends Pair<? extends VectorType,DataType>> implements Serializable
  - Serialized Fields
    - num
```
int num
```
      Number of elements in this subtree.
    - value
```
Pair<FirstType,SecondType> value
```
      VectorType,DataType value for this node of the subtree.
    - parent
```
KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> parent
```
      Parent of this node of the subtree.
    - leftChild
```
KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> leftChild
```
      Left child of this subtree
    - rightChild
```
KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> rightChild
```
      Right child of this subtree.
    - comparator
```
KDTree.PairFirstVectorizableIndexComparator comparator
```
      Comparator of this node to determine less than, greater than, or equality.
- Class gov.sandia.cognition.math.geometry.KDTree.Neighborhood.Neighbor extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - pair
```
Pair<FirstType,SecondType> pair
```
      Pair to store.
    - distance
```
double distance
```
      Distance associated with this value.
- Class gov.sandia.cognition.math.geometry.KDTree.PairFirstVectorizableIndexComparator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - comparator
```
VectorizableIndexComparator comparator
```
      Embedded comparator for the Vectorizable argument.
- Class gov.sandia.cognition.math.geometry.Quadtree extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - splitThreshold
```
int splitThreshold
```
      The minimum number of items allowed in a leaf node. If there are more than this, then a node must be split. This number must be greater than zero.
    - items
```
java.util.LinkedList<E> items
```
      All of the items in the tree. It should never be null.
    - initalBounds
```
java.awt.geom.Rectangle2D.Double initalBounds
```
      The initial bounds for the tree. This may be null if they are not specified.
    - root
```
Quadtree.Node root
```
      The root node of the tree. It should never be null.
- Class gov.sandia.cognition.math.geometry.Quadtree.Node extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - parent
```
Quadtree.Node parent
```
      The parent of this node in the tree. Null only for the root node.
    - bounds
```
java.awt.geom.Rectangle2D.Double bounds
```
      The two-dimensional bounds for this node. This is only null if it is the root node and has no elements and no default bounds.
    - depth
```
int depth
```
      The depth of this node in the tree.
    - localItems
```
java.util.LinkedList<E> localItems
```
      The local items stored at this node.
    - lowerRight
```
Quadtree.Node lowerRight
```
      The child for the lower-right quadrant of this node.
    - lowerLeft
```
Quadtree.Node lowerLeft
```
      The child for the lower-left quadrant of this node.
    - upperLeft
```
Quadtree.Node upperLeft
```
      The child for the upper-left quadrant of this node.
    - upperRight
```
Quadtree.Node upperRight
```
      The child for the upper-right quadrant of this node.
    - children
```
java.util.ArrayList<E> children
```
      The list of children for this node. Null to indicate that it has no children and thus is a leaf node.
Package gov.sandia.cognition.math.matrix
- Class gov.sandia.cognition.math.matrix.AbstractMatrix extends AbstractRing<Matrix> implements Serializable
- Class gov.sandia.cognition.math.matrix.AbstractVector extends AbstractVectorSpace<Vector,VectorEntry> implements Serializable
- Class gov.sandia.cognition.math.matrix.AbstractVectorSpace extends AbstractRing<VectorType extends VectorSpace<VectorType,? extends EntryType>> implements Serializable
- Class gov.sandia.cognition.math.matrix.DefaultInfiniteVector extends AbstractMutableDoubleMap<KeyType> implements Serializable
- Class gov.sandia.cognition.math.matrix.DefaultVectorFactoryContainer extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The vector factory used to create new vectors.
- Class gov.sandia.cognition.math.matrix.DimensionalityMismatchException extends java.lang.RuntimeException implements Serializable
- Class gov.sandia.cognition.math.matrix.MatrixFactory extends java.lang.Object implements Serializable
- Class gov.sandia.cognition.math.matrix.NumericalDifferentiator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - delta
```
double delta
```
      Value for x-value differencing, must be greater than 0.0
    - internalFunction
```
Evaluator<InputType,OutputType> internalFunction
```
      Internal function to numerically differencing.
- Class gov.sandia.cognition.math.matrix.NumericalDifferentiator.DoubleJacobian extends NumericalDifferentiator<java.lang.Double,java.lang.Double,java.lang.Double> implements Serializable
- Class gov.sandia.cognition.math.matrix.NumericalDifferentiator.MatrixJacobian extends NumericalDifferentiator<Vector,Vector,Matrix> implements Serializable
- Class gov.sandia.cognition.math.matrix.NumericalDifferentiator.VectorJacobian extends NumericalDifferentiator<Vector,java.lang.Double,Vector> implements Serializable
- Class gov.sandia.cognition.math.matrix.SparseVectorFactory extends VectorFactory<VectorType extends Vector> implements Serializable
- Class gov.sandia.cognition.math.matrix.VectorFactory extends java.lang.Object implements Serializable
- Class gov.sandia.cognition.math.matrix.VectorizableIndexComparator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - index
```
int index
```
      Index to compare against.
Package gov.sandia.cognition.math.matrix.custom
- Class gov.sandia.cognition.math.matrix.custom.CustomDenseMatrixFactory extends MatrixFactory<DenseMatrix> implements Serializable
- Class gov.sandia.cognition.math.matrix.custom.CustomDenseVectorFactory extends VectorFactory<DenseVector> implements Serializable
- Class gov.sandia.cognition.math.matrix.custom.CustomDiagonalMatrixFactory extends MatrixFactory<DiagonalMatrix> implements Serializable
- Class gov.sandia.cognition.math.matrix.custom.CustomSparseMatrixFactory extends MatrixFactory<SparseMatrix> implements Serializable
- Class gov.sandia.cognition.math.matrix.custom.CustomSparseVectorFactory extends VectorFactory<SparseVector> implements Serializable
- Class gov.sandia.cognition.math.matrix.custom.DenseMatrix extends gov.sandia.cognition.math.matrix.custom.BaseMatrix implements Serializable
  - Serialized Fields
    - rows
```
DenseVector[] rows
```
      The rows of the matrix stored as dense vectors
- Class gov.sandia.cognition.math.matrix.custom.DenseVector extends gov.sandia.cognition.math.matrix.custom.BaseVector implements Serializable
  - Serialized Fields
    - values
```
double[] values
```
      The data is stored in this vector.
- Class gov.sandia.cognition.math.matrix.custom.DiagonalMatrix extends gov.sandia.cognition.math.matrix.custom.BaseMatrix implements Serializable
  - Serialized Fields
    - diagonal
```
double[] diagonal
```
      The elements down the diagonal
- Class gov.sandia.cognition.math.matrix.custom.ParallelSparseMatrix extends SparseMatrix implements Serializable
  - Serialized Fields
    - numThreads
```
int numThreads
```
      This stores the number of threads to use for all operations.
- Class gov.sandia.cognition.math.matrix.custom.SparseMatrix extends gov.sandia.cognition.math.matrix.custom.BaseMatrix implements Serializable
  - Serialization Methods
    - readObject
```
private void readObject(java.io.ObjectInputStream ois)
                 throws java.io.IOException,
                        java.lang.ClassNotFoundException
```
      Called by de-serialization (through the magic of Java reflect) and shouldn't be called by anyone else.
      
      Throws:
      
      java.io.IOException - If there's a problem
      
      java.lang.ClassNotFoundException - If there's a problem
    - writeObject
```
private void writeObject(java.io.ObjectOutputStream oos)
                  throws java.io.IOException
```
      Called by serialization (through the magic of Java reflection) and shouldn't be called by anyone else.
      
      Throws:
      
      java.io.IOException - If there's a problem
  - Serialized Fields
    - numRows
```
int numRows
```
      The number of rows in the matrix. This is stored explicitly here (vs. using the implicit storage in the sparse rows or compressed Yale format) because of the fact that this switches between compressed Yale and sparse row formats at runtime.
    - numCols
```
int numCols
```
      The number of columns in the matrix. This is stored explicitly here (vs. using the implicit storage in the sparse rows) because of the fact that this switches between compressed Yale (which doesn't store the number of columns anywhere) and sparse row formats at runtime.
    - rows
```
SparseVector[] rows
```
      The sparse vector representation of the matrix. Can be out-of-sync with latest values (or null) depending on if the compressed Yale format is the current representation. See the isCompresed method to tell which format is current.
    - values
```
double[] values
```
      Part of the compressed Yale format. Generally only stores the non-zero elements of the matrix (to optimize some of the methods herein, some zero elements may be in vals). Will be null when the matrix is not compressed.
    - firstIndicesForRows
```
int[] firstIndicesForRows
```
      Part of the compressed Yale format. Stores the first index into vals for each row in the matrix. Has length of numRows + 1. Will be null when the matrix is not compressed.
    - columnIndices
```
int[] columnIndices
```
      Part of the compressed Yale format. Has the same length of vals. This specifies which column each element of vals is in. Will be null when the matrix is not compressed.
- Class gov.sandia.cognition.math.matrix.custom.SparseVector extends gov.sandia.cognition.math.matrix.custom.BaseVector implements Serializable
  - Serialized Fields
    - dimensionality
```
int dimensionality
```
      The vector length
    - elements
```
java.util.TreeMap<K,V> elements
```
      The index-to-value map
    - values
```
double[] values
```
      Compressed version of the data: The values. Similar to the Yale format for sparse matrices.
    - indices
```
int[] indices
```
      Compressed version of the data: The locations. Similar to the Yale format for sparse matrices.
Package gov.sandia.cognition.math.matrix.decomposition
- Class gov.sandia.cognition.math.matrix.decomposition.EigenvectorPowerIteration extends AbstractCloneableSerializable implements Serializable
Package gov.sandia.cognition.math.matrix.mtj
- Class gov.sandia.cognition.math.matrix.mtj.AbstractMTJMatrix extends AbstractMatrix implements Serializable
- Class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector extends AbstractVector implements Serializable
- Class gov.sandia.cognition.math.matrix.mtj.AbstractSparseMatrix extends AbstractMTJMatrix implements Serializable
- Class gov.sandia.cognition.math.matrix.mtj.DenseMatrix extends AbstractMTJMatrix implements Serializable
  - Serialization Methods
    - readObject
```
private void readObject(java.io.ObjectInputStream in)
                 throws java.io.IOException,
                        java.lang.ClassNotFoundException
```
      Reads in a serialized class from the specified stream
      
      Throws:
      
      java.io.IOException - On bad read
      
      java.lang.ClassNotFoundException - if next object isn't DenseMatrix
    - writeObject
```
private void writeObject(java.io.ObjectOutputStream out)
                  throws java.io.IOException
```
      Writes a DenseMatrix out to a serialized file
      
      Throws:
      
      java.io.IOException - On bad write
- Class gov.sandia.cognition.math.matrix.mtj.DenseMatrixFactoryMTJ extends MatrixFactory<DenseMatrix> implements Serializable
- Class gov.sandia.cognition.math.matrix.mtj.DenseVector extends AbstractMTJVector implements Serializable
  - Serialization Methods
    - readObject
```
private void readObject(java.io.ObjectInputStream in)
                 throws java.io.IOException,
                        java.lang.ClassNotFoundException
```
      Reads in a serialized class from the specified stream
      
      Throws:
      
      java.io.IOException - On bad read
      
      java.lang.ClassNotFoundException - if next object isn't DenseVector
    - writeObject
```
private void writeObject(java.io.ObjectOutputStream out)
                  throws java.io.IOException
```
      Writes a DenseVector out to a serialized stream (usually file)
      
      Throws:
      
      java.io.IOException - On bad write
- Class gov.sandia.cognition.math.matrix.mtj.DenseVectorFactoryMTJ extends VectorFactory<DenseVector> implements Serializable
- Class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixFactoryMTJ extends MatrixFactory<DiagonalMatrixMTJ> implements Serializable
- Class gov.sandia.cognition.math.matrix.mtj.DiagonalMatrixMTJ extends AbstractMTJMatrix implements Serializable
  - Serialization Methods
    - readObject
```
private void readObject(java.io.ObjectInputStream in)
                 throws java.io.IOException,
                        java.lang.ClassNotFoundException
```
      Reads in a serialized class from the specified stream
      
      Throws:
      
      java.io.IOException - On bad read
      
      java.lang.ClassNotFoundException - if next object isn't DenseMatrix
    - writeObject
```
private void writeObject(java.io.ObjectOutputStream out)
                  throws java.io.IOException
```
      Writes a DenseMatrix out to a serialized file
      
      Throws:
      
      java.io.IOException - On bad write
- Class gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix extends AbstractSparseMatrix implements Serializable
  - Serialization Methods
    - readObject
```
private void readObject(java.io.ObjectInputStream in)
                 throws java.io.IOException,
                        java.lang.ClassNotFoundException
```
      Custom deserialization is needed.
      
      Throws:
      
      java.io.IOException - If there is an error with the stream.
      
      java.lang.ClassNotFoundException - If a class used by this one cannot be found.
    - writeObject
```
private void writeObject(java.io.ObjectOutputStream out)
                  throws java.io.IOException
```
      Custom serialization is needed.
      
      Throws:
      
      java.io.IOException - If there is an error writing to the stream.
- Class gov.sandia.cognition.math.matrix.mtj.SparseMatrix extends SparseRowMatrix implements Serializable
- Class gov.sandia.cognition.math.matrix.mtj.SparseMatrixFactoryMTJ extends MatrixFactory<SparseMatrix> implements Serializable
- Class gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix extends AbstractSparseMatrix implements Serializable
  - Serialization Methods
    - readObject
```
private void readObject(java.io.ObjectInputStream in)
                 throws java.io.IOException,
                        java.lang.ClassNotFoundException
```
      Custom deserialization is needed.
      
      Throws:
      
      java.io.IOException - If there is an error with the stream.
      
      java.lang.ClassNotFoundException - If a class used by this one cannot be found.
    - writeObject
```
private void writeObject(java.io.ObjectOutputStream out)
                  throws java.io.IOException
```
      Custom serialization is needed.
      
      Throws:
      
      java.io.IOException - If there is an error writing to the stream.
- Class gov.sandia.cognition.math.matrix.mtj.SparseVector extends AbstractMTJVector implements Serializable
  - Serialization Methods
    - readObject
```
private void readObject(java.io.ObjectInputStream in)
                 throws java.io.IOException,
                        java.lang.ClassNotFoundException
```
      This method provides custom deserialization for the class since the MTJ class does not implement Serializable.
      
      Throws:
      
      java.io.IOException - If there is an error reading the object.
      
      java.lang.ClassNotFoundException - If a class cannot be found.
    - writeObject
```
private void writeObject(java.io.ObjectOutputStream out)
                  throws java.io.IOException
```
      This method provides custom serialization for the class since the MTJ class does not implement Serializable.
      
      Throws:
      
      java.io.IOException - If there is an error with the stream.
- Class gov.sandia.cognition.math.matrix.mtj.SparseVectorFactoryMTJ extends SparseVectorFactory<SparseVector> implements Serializable
- Class gov.sandia.cognition.math.matrix.mtj.Vector1 extends DenseVector implements Serializable
- Class gov.sandia.cognition.math.matrix.mtj.Vector2 extends DenseVector implements Serializable
- Class gov.sandia.cognition.math.matrix.mtj.Vector3 extends DenseVector implements Serializable
Package gov.sandia.cognition.math.matrix.mtj.decomposition
- Class gov.sandia.cognition.math.matrix.mtj.decomposition.CholeskyDecompositionMTJ extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - R
```
DenseMatrix R
```
      Cholesky factor, such that R.transpose().times( R ) equals the original matrix
Package gov.sandia.cognition.math.signals
- Class gov.sandia.cognition.math.signals.AutoRegressiveMovingAverageFilter extends AbstractStatefulEvaluator<java.lang.Double,java.lang.Double,DefaultPair<FiniteCapacityBuffer<java.lang.Double>,FiniteCapacityBuffer<java.lang.Double>>> implements Serializable
  - Serialized Fields
    - movingAverageCoefficients
```
Vector movingAverageCoefficients
```
      Coefficients of the moving-average filter. Element 0 is applied to the most-recent input, Element 1 is applied to the second-most-recent, and so forth. The dimensionality of the Vector is the order of the filter.
    - autoRegressiveCoefficients
```
Vector autoRegressiveCoefficients
```
      Coefficients of the autoregressive filter. Element 0 is applied to the most-recent output, Element 1 is applied to the second-most-recent, and so forth. The dimensionality of the Vector is the order of the filter.
- Class gov.sandia.cognition.math.signals.FourierTransform extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.math.signals.FourierTransform.Inverse extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.math.signals.LinearDynamicalSystem extends AbstractStatefulEvaluator<Vector,Vector,Vector> implements Serializable
  - Serialized Fields
    - A
```
Matrix A
```
      System (Jacobian) matrix. Must be square.
    - B
```
Matrix B
```
      Input-gain matrix. Columns must equal A's rows.
    - C
```
Matrix C
```
      Output-selector matrix. Columns must equal A's rows.
- Class gov.sandia.cognition.math.signals.MovingAverageFilter extends AbstractStatefulEvaluator<java.lang.Double,java.lang.Double,FiniteCapacityBuffer<java.lang.Double>> implements Serializable
  - Serialized Fields
    - movingAverageCoefficients
```
Vector movingAverageCoefficients
```
      Coefficients of the moving-average filter. Element 0 is applied to the most-recent input, Element 1 is applied to the second-most-recent, and so forth. The dimensionality of the Vector is the order of the filter.
- Class gov.sandia.cognition.math.signals.PIDController extends AbstractStatefulEvaluator<java.lang.Double,java.lang.Double,PIDController.State> implements Serializable
  - Serialized Fields
    - targetInput
```
double targetInput
```
      Set point target to achieve at steady-state.
    - proportionalGain
```
double proportionalGain
```
      Proportional-error gain.
    - integralGain
```
double integralGain
```
      Integral-error gain.
    - derivativeGain
```
double derivativeGain
```
      Derivative-error gain.
- Class gov.sandia.cognition.math.signals.PIDController.State extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - lastErr
```
double lastErr
```
      Last error.
    - errSum
```
double errSum
```
      Sum of all errors.
Package gov.sandia.cognition.statistics
- Class gov.sandia.cognition.statistics.AbstractClosedFormIntegerDistribution extends AbstractClosedFormUnivariateDistribution<java.lang.Number> implements Serializable
- Class gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution extends AbstractClosedFormUnivariateDistribution<java.lang.Double> implements Serializable
- Class gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution extends AbstractDistribution<NumberType extends java.lang.Number> implements Serializable
- Class gov.sandia.cognition.statistics.AbstractDataDistribution extends AbstractMutableDoubleMap<KeyType> implements Serializable
- Class gov.sandia.cognition.statistics.AbstractDistribution extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.AbstractIncrementalEstimator extends AbstractBatchAndIncrementalLearner<DataType,SufficientStatisticsType extends SufficientStatistic<DataType,DistributionType>> implements Serializable
- Class gov.sandia.cognition.statistics.AbstractRandomVariable extends AbstractRing<RandomVariable<DataType>> implements Serializable
- Class gov.sandia.cognition.statistics.AbstractSufficientStatistic extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - count
```
long count
```
      Number of data points used to create this SufficientStatistic
- Class gov.sandia.cognition.statistics.DefaultDistributionParameter extends AbstractNamed implements Serializable
  - Serialized Fields
    - conditionalDistribution
```
ClosedFormDistribution<DataType> conditionalDistribution
```
      Distribution from which to pull the parameters.
- Class gov.sandia.cognition.statistics.UnivariateRandomVariable extends AbstractRandomVariable<java.lang.Number> implements Serializable
  - Serialized Fields
    - numSamples
```
int numSamples
```
      Number of samples to draw from the distribution to perform the empirical algebra approximation.
    - random
```
java.util.Random random
```
      Random number generator used for sampling the distribution.
    - distribution
```
UnivariateDistribution<NumberType extends java.lang.Number> distribution
```
      Scalar distribution that backs the random variable, from which samples will be drawn to approximate the distribution during algebra.
Package gov.sandia.cognition.statistics.bayesian
- Class gov.sandia.cognition.statistics.bayesian.AbstractBayesianParameter extends AbstractNamed implements Serializable
  - Serialized Fields
    - conditionalDistribution
```
ClosedFormDistribution<DataType> conditionalDistribution
```
      Distribution from which to pull the parameters.
    - parameterPrior
```
Distribution<DataType> parameterPrior
```
      Distribution of values that the parameter is assumed to take.
- Class gov.sandia.cognition.statistics.bayesian.AbstractKalmanFilter extends AbstractBatchAndIncrementalLearner<Vector,MultivariateGaussian> implements Serializable
  - Serialized Fields
    - currentInput
```
Vector currentInput
```
      Current input to the model.
    - modelCovariance
```
Matrix modelCovariance
```
      Covariance associated with the system's model.
    - measurementCovariance
```
Matrix measurementCovariance
```
      Covariance associated with the measurements.
- Class gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo extends AbstractAnytimeBatchLearner<java.util.Collection<? extends ObservationType>,DataDistribution<ParameterType>> implements Serializable
  - Serialized Fields
    - random
```
java.util.Random random
```
      Random number generator.
    - burnInIterations
```
int burnInIterations
```
      The number of iterations that must transpire before the algorithm begins collection the samples.
    - iterationsPerSample
```
int iterationsPerSample
```
      The number of iterations that must transpire between capturing samples from the distribution.
    - currentParameter
```
java.lang.Object currentParameter
```
      The current parameters in the random walk.
    - previousParameter
```
java.lang.Object previousParameter
```
      The previous parameter in the random walk.
- Class gov.sandia.cognition.statistics.bayesian.AbstractParticleFilter extends AbstractBatchAndIncrementalLearner<ObservationType,DataDistribution<ParameterType>> implements Serializable
  - Serialized Fields
    - updater
```
ParticleFilter.Updater<ObservationType,ParameterType> updater
```
      Updates the particle given an existing particle.
    - numParticles
```
int numParticles
```
      Number of particles in the filter.
- Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - logFunction
```
AdaptiveRejectionSampling.LogEvaluator<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>> logFunction
```
      Logarithm of the function that we want to evaluate
    - points
```
java.util.ArrayList<E> points
```
      Input-output point pairs, sorted in ascending order by their x-axis value
    - maxNumPoints
```
int maxNumPoints
```
      Maximum number of points that will be stored
    - minSupport
```
double minSupport
```
      Minimum support (x-value) of the logFunction
    - maxSupport
```
double maxSupport
```
      Maximum support (x-value) of the logFunction
    - upperEnvelope
```
AdaptiveRejectionSampling.UpperEnvelope upperEnvelope
```
      Upper envelope of the logFunction
    - lowerEnvelope
```
AdaptiveRejectionSampling.LowerEnvelope lowerEnvelope
```
      Lower envelope of the logFunction
- Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.AbstractEnvelope extends AbstractUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - lines
```
java.util.ArrayList<E> lines
```
      Line segments that comprise the envelope
- Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LineSegment extends PolynomialFunction.Linear implements Serializable
  - Serialized Fields
    - left
```
double left
```
      Left (minimum) x-axis value
    - right
```
double right
```
      Right (maximum) x-axis value
- Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LogEvaluator extends AbstractUnivariateScalarFunction implements Serializable
  - Serialized Fields
    - function
```
Evaluator<InputType,OutputType> function
```
      Evaluator to wrap and compute the natural logarithm of.
- Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.LowerEnvelope extends AdaptiveRejectionSampling.AbstractEnvelope implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.PDFLogEvaluator extends AdaptiveRejectionSampling.LogEvaluator<ProbabilityFunction<java.lang.Double>> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.Point extends DefaultInputOutputPair<java.lang.Double,java.lang.Double> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.AdaptiveRejectionSampling.UpperEnvelope extends AdaptiveRejectionSampling.AbstractEnvelope implements Serializable
  - Serialized Fields
    - segmentCDF
```
double[] segmentCDF
```
      Cumulative sums of the normalized weights of the lines... This is automatically computed by computeSegments method.
- Class gov.sandia.cognition.statistics.bayesian.BayesianCredibleInterval extends ConfidenceInterval implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - outputVariance
```
double outputVariance
```
      Assumed known variance of the outputs (measurements), must be greater than zero.
    - weightPrior
```
MultivariateGaussian weightPrior
```
      Prior distribution of the weights, typically a zero-mean, diagonal-variance distribution.
- Class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.IncrementalEstimator extends BayesianLinearRegression implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.IncrementalEstimator.SufficientStatistic extends AbstractSufficientStatistic<InputOutputPair<? extends Vectorizable,java.lang.Double>,MultivariateGaussian> implements Serializable
  - Serialized Fields
    - z
```
Vector z
```
      "z" statistic, proportional to the mean
    - covarianceInverse
```
Matrix covarianceInverse
```
      Covariance inverse, sometimes called "precision"
- Class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression.PredictiveDistribution extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - posterior
```
MultivariateGaussian posterior
```
      Posterior distribution of the weights given the data.
- Class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - weightPrior
```
MultivariateGaussian weightPrior
```
      Prior distribution of the weights, typically a zero-mean, diagonal-variance distribution.
    - outputVariance
```
InverseGammaDistribution outputVariance
```
      Distribution of the output (measurement) variance
- Class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.IncrementalEstimator extends BayesianRobustLinearRegression implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.IncrementalEstimator.SufficientStatistic extends AbstractSufficientStatistic<InputOutputPair<? extends Vectorizable,java.lang.Double>,MultivariateGaussianInverseGammaDistribution> implements Serializable
  - Serialized Fields
    - outputSumSquared
```
double outputSumSquared
```
      Sum of the output squared
    - z
```
Vector z
```
      "z" statistic, proportional to the mean
    - covarianceInverse
```
Matrix covarianceInverse
```
      Covariance inverse, sometimes called "precision"
- Class gov.sandia.cognition.statistics.bayesian.BayesianRobustLinearRegression.PredictiveDistribution extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - posterior
```
MultivariateGaussianInverseGammaDistribution posterior
```
      Posterior distribution of the weights given the data.
- Class gov.sandia.cognition.statistics.bayesian.DefaultBayesianParameter extends DefaultDistributionParameter<ParameterType,ConditionalType extends ClosedFormDistribution<?>> implements Serializable
  - Serialized Fields
    - parameterPrior
```
Distribution<DataType> parameterPrior
```
      Distribution of values that the parameter is assumed to take.
- Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel extends AbstractMarkovChainMonteCarlo<ObservationType,DirichletProcessMixtureModel.Sample<ObservationType>> implements Serializable
  - Serialized Fields
    - updater
```
DirichletProcessMixtureModel.Updater<ObservationType> updater
```
      Creates the clusters and predictive prior distributions
    - numInitialClusters
```
int numInitialClusters
```
      Number of clusters to initialize
    - reestimateAlpha
```
boolean reestimateAlpha
```
      Flag to automatically re-estimate the alpha parameter
    - initialAlpha
```
double initialAlpha
```
      Initial value of alpha, the concentration parameter of the Dirichlet Process
- Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.DPMMCluster extends DefaultCluster<ObservationType> implements Serializable
  - Serialized Fields
    - probabilityFunction
```
ProbabilityFunction<DataType> probabilityFunction
```
      Probability function describing the assigned data
- Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.DPMMLogConditional extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - logConditional
```
double logConditional
```
      log conditional likelihood
- Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.MultivariateMeanCovarianceUpdater extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - estimator
```
MultivariateGaussianMeanCovarianceBayesianEstimator estimator
```
      Bayesian estimator for the parameters
- Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.MultivariateMeanUpdater extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - estimator
```
MultivariateGaussianMeanBayesianEstimator estimator
```
      Bayesian estimator for the parameters
- Class gov.sandia.cognition.statistics.bayesian.DirichletProcessMixtureModel.Sample extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - alpha
```
double alpha
```
      Scaling parameter which defines the strength of the base distribution, must be greater than zero.
    - clusters
```
java.util.ArrayList<E> clusters
```
      Point mass realizations from the base distribution.
    - posteriorLogLikelihood
```
java.lang.Double posteriorLogLikelihood
```
      Posterior log likelihood of the sample
- Class gov.sandia.cognition.statistics.bayesian.ExtendedKalmanFilter extends AbstractKalmanFilter implements Serializable
  - Serialized Fields
    - motionModel
```
StatefulEvaluator<InputType,OutputType,StateType extends CloneableSerializable> motionModel
```
      Model that determines how inputs and the previous state are updated.
    - observationModel
```
Evaluator<InputType,OutputType> observationModel
```
      Model that determines how the state is observed.
- Class gov.sandia.cognition.statistics.bayesian.GaussianProcessRegression extends DefaultKernelContainer<InputType> implements Serializable
  - Serialized Fields
    - outputVariance
```
double outputVariance
```
      Assumed known variance of the outputs (measurements), must be greater than or equal to zero.
- Class gov.sandia.cognition.statistics.bayesian.GaussianProcessRegression.PredictiveDistribution extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - inputs
```
java.util.ArrayList<E> inputs
```
      Inputs that we've condition on.
    - posterior
```
MultivariateGaussian posterior
```
      Posterior distribution of the Gaussian process given the data.
- Class gov.sandia.cognition.statistics.bayesian.ImportanceSampling extends AbstractRandomized implements Serializable
  - Serialized Fields
    - updater
```
ImportanceSampling.Updater<ObservationType,ParameterType> updater
```
      Updater for the ImportanceSampling algorithm.
    - numSamples
```
int numSamples
```
      Number of samples.
- Class gov.sandia.cognition.statistics.bayesian.ImportanceSampling.DefaultUpdater extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - conjuctive
```
BayesianParameter<ParameterType,ConditionalType extends Distribution<?>,PriorType extends Distribution<ParameterType>> conjuctive
```
      Defines the parameter that connects the conditional and prior distributions.
- Class gov.sandia.cognition.statistics.bayesian.KalmanFilter extends AbstractKalmanFilter implements Serializable
  - Serialized Fields
    - model
```
LinearDynamicalSystem model
```
      Motion model of the underlying system.
- Class gov.sandia.cognition.statistics.bayesian.MetropolisHastingsAlgorithm extends AbstractMarkovChainMonteCarlo<ObservationType,ParameterType> implements Serializable
  - Serialized Fields
    - currentLogLikelihood
```
double currentLogLikelihood
```
      Log Likelihood of the current parameters.
    - updater
```
MetropolisHastingsAlgorithm.Updater<ObservationType,ParameterType> updater
```
      The object that makes proposal samples from the current location.
- Class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel extends DirichletProcessMixtureModel<ObservationType> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel.ClusterUpdaterTask extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - observations
```
java.util.Collection<E> observations
```
      Observations that comprise the cluster
    - localUpdater
```
DirichletProcessMixtureModel.Updater<ObservationType> localUpdater
```
      Local clone of the updater, needed to ensure thread safety
- Class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel.ObservationAssignmentTask extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - observations
```
java.util.Collection<E> observations
```
      Observations to assign
    - weights
```
double[] weights
```
      Weights that are re-used
    - assignments
```
java.util.ArrayList<E> assignments
```
      Resulting assignments
    - logConditional
```
DirichletProcessMixtureModel.DPMMLogConditional logConditional
```
      Log conditional of the previous sample
- Class gov.sandia.cognition.statistics.bayesian.RejectionSampling extends AbstractRandomized implements Serializable
  - Serialized Fields
    - numSamples
```
int numSamples
```
      Number of samples.
    - updater
```
RejectionSampling.Updater<ObservationType,ParameterType> updater
```
      Updater for the ImportanceSampling algorithm.
- Class gov.sandia.cognition.statistics.bayesian.RejectionSampling.DefaultUpdater extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - conjuctive
```
BayesianParameter<ParameterType,ConditionalType extends Distribution<?>,PriorType extends Distribution<ParameterType>> conjuctive
```
      Defines the parameter that connects the conditional and prior distributions.
    - scale
```
java.lang.Double scale
```
      Scale factor to multiply the sampler function by to envelop the conjunctive distribution.
    - sampler
```
ProbabilityFunction<DataType> sampler
```
      Distribution from which we sample and envelop the conjunctive distribution.
    - proposals
```
int proposals
```
      Number of proposals suggested
- Class gov.sandia.cognition.statistics.bayesian.SamplingImportanceResamplingParticleFilter extends AbstractParticleFilter<ObservationType,ParameterType> implements Serializable
  - Serialized Fields
    - particlePctThreadhold
```
double particlePctThreadhold
```
      Percentage of effective particles, below which we resample.
Package gov.sandia.cognition.statistics.bayesian.conjugate
- Class gov.sandia.cognition.statistics.bayesian.conjugate.AbstractConjugatePriorBayesianEstimator extends AbstractBatchAndIncrementalLearner<ObservationType,BeliefType extends ClosedFormDistribution<ParameterType>> implements Serializable
  - Serialized Fields
    - parameter
```
BayesianParameter<ParameterType,ConditionalType extends Distribution<?>,PriorType extends Distribution<ParameterType>> parameter
```
      Bayesian hyperparameter relationship between the conditional distribution and the conjugate prior distribution.
- Class gov.sandia.cognition.statistics.bayesian.conjugate.BernoulliBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<java.lang.Number,java.lang.Double,BernoulliDistribution,BetaDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.BernoulliBayesianEstimator.Parameter extends AbstractBayesianParameter<java.lang.Double,BernoulliDistribution,BetaDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<java.lang.Number,java.lang.Double,BinomialDistribution,BetaDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.BinomialBayesianEstimator.Parameter extends AbstractBayesianParameter<java.lang.Double,BinomialDistribution,BetaDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.ExponentialBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<java.lang.Double,java.lang.Double,ExponentialDistribution,GammaDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.ExponentialBayesianEstimator.Parameter extends AbstractBayesianParameter<java.lang.Double,ExponentialDistribution,GammaDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.GammaInverseScaleBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<java.lang.Double,java.lang.Double,GammaDistribution,GammaDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.GammaInverseScaleBayesianEstimator.Parameter extends AbstractBayesianParameter<java.lang.Double,GammaDistribution,GammaDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Vector,Vector,MultinomialDistribution,DirichletDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.MultinomialBayesianEstimator.Parameter extends AbstractBayesianParameter<Vector,MultinomialDistribution,DirichletDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Vector,Vector,MultivariateGaussian,MultivariateGaussian> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanBayesianEstimator.Parameter extends AbstractBayesianParameter<Vector,MultivariateGaussian,MultivariateGaussian> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanCovarianceBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<Vector,Matrix,MultivariateGaussian,NormalInverseWishartDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.MultivariateGaussianMeanCovarianceBayesianEstimator.Parameter extends AbstractBayesianParameter<Matrix,MultivariateGaussian,NormalInverseWishartDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<java.lang.Number,java.lang.Double,PoissonDistribution,GammaDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.PoissonBayesianEstimator.Parameter extends AbstractBayesianParameter<java.lang.Double,PoissonDistribution,GammaDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.UniformDistributionBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<java.lang.Double,java.lang.Double,UniformDistribution,ParetoDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.UniformDistributionBayesianEstimator.Parameter extends AbstractBayesianParameter<java.lang.Double,UniformDistribution,ParetoDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<java.lang.Double,java.lang.Double,UnivariateGaussian,UnivariateGaussian> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanBayesianEstimator.Parameter extends AbstractBayesianParameter<java.lang.Double,UnivariateGaussian,UnivariateGaussian> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanVarianceBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<java.lang.Double,Vector,UnivariateGaussian,NormalInverseGammaDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.bayesian.conjugate.UnivariateGaussianMeanVarianceBayesianEstimator.Parameter extends AbstractBayesianParameter<Vector,UnivariateGaussian,NormalInverseGammaDistribution> implements Serializable
Package gov.sandia.cognition.statistics.distribution
- Class gov.sandia.cognition.statistics.distribution.BernoulliDistribution extends AbstractClosedFormIntegerDistribution implements Serializable
  - Serialized Fields
    - p
```
double p
```
      Bernoulli parameter, where the distribution takes value "1" with probability "p" and value "0" with probability 1-p.
- Class gov.sandia.cognition.statistics.distribution.BernoulliDistribution.CDF extends BernoulliDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.BernoulliDistribution.PMF extends BernoulliDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution extends AbstractClosedFormIntegerDistribution implements Serializable
  - Serialized Fields
    - n
```
int n
```
      Number of observations, similar to the Binomial N, must be greater than zero
    - shape
```
double shape
```
      Shape, similar to the beta parameter shape, must be greater than zero
    - scale
```
double scale
```
      Scale, similar to the beta parameter scale, must be greater than zero
- Class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.CDF extends BetaBinomialDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.MomentMatchingEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.BetaBinomialDistribution.PMF extends BetaBinomialDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.BetaDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - alpha
```
double alpha
```
      Alpha shape parameter, must be greater than 0 (typically greater than 1)
    - beta
```
double beta
```
      Alpha shape parameter, must be greater than 0 (typically greater than 1)
- Class gov.sandia.cognition.statistics.distribution.BetaDistribution.CDF extends BetaDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.BetaDistribution.MomentMatchingEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.BetaDistribution.PDF extends BetaDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.BetaDistribution.WeightedMomentMatchingEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.BinomialDistribution extends AbstractClosedFormIntegerDistribution implements Serializable
  - Serialized Fields
    - N
```
int N
```
      Total number of experiments, must be greater than zero
    - p
```
double p
```
      Probability of a positive outcome (Bernoulli probability), [0,1]
- Class gov.sandia.cognition.statistics.distribution.BinomialDistribution.CDF extends BinomialDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.BinomialDistribution.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.BinomialDistribution.PMF extends BinomialDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.CategoricalDistribution extends AbstractDistribution<Vector> implements Serializable
  - Serialized Fields
    - parameters
```
Vector parameters
```
      Parameters of the multinomial distribution, must be at least 2-dimensional and each element must be nonnegative.
- Class gov.sandia.cognition.statistics.distribution.CategoricalDistribution.PMF extends CategoricalDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.CauchyDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - location
```
double location
```
      Central location (also the median and mode) of the distribution.
    - scale
```
double scale
```
      Scale of the distribution, must be greater than zero.
- Class gov.sandia.cognition.statistics.distribution.CauchyDistribution.CDF extends CauchyDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.CauchyDistribution.PDF extends CauchyDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess extends AbstractDistribution<Vector> implements Serializable
  - Serialized Fields
    - alpha
```
double alpha
```
      CRP concentration parameter, must be greater than zero.
    - numCustomers
```
int numCustomers
```
      Total number of customers that we will arrange around tables, must be greater than zero.
- Class gov.sandia.cognition.statistics.distribution.ChineseRestaurantProcess.PMF extends ChineseRestaurantProcess implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - degreesOfFreedom
```
double degreesOfFreedom
```
      Number of degrees of freedom in the distribution, must be greater than 0.0
- Class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution.CDF extends ChiSquareDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ChiSquareDistribution.PDF extends ChiSquareDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.DataCountTreeSetBinnedMapHistogram extends DefaultDataDistribution<ValueType extends java.lang.Comparable<? super ValueType>> implements Serializable
  - Serialized Fields
    - binner
```
TreeSetBinner<ValueType extends java.lang.Comparable<? super ValueType>> binner
```
      The binner used to map values to bins
- Class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution extends AbstractDataDistribution<KeyType> implements Serializable
  - Serialized Fields
    - total
```
double total
```
      Total of the counts in the distribution
- Class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.DefaultFactory extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - initialDomainCapacity
```
int initialDomainCapacity
```
      The initial domain capacity.
- Class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.Estimator extends AbstractBatchAndIncrementalLearner<KeyType,DefaultDataDistribution.PMF<KeyType>> implements Serializable
- Class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.PMF extends DefaultDataDistribution<KeyType> implements Serializable
- Class gov.sandia.cognition.statistics.distribution.DefaultDataDistribution.WeightedEstimator extends AbstractBatchAndIncrementalLearner<WeightedValue<? extends KeyType>,DefaultDataDistribution.PMF<KeyType>> implements Serializable
- Class gov.sandia.cognition.statistics.distribution.DeterministicDistribution extends AbstractClosedFormUnivariateDistribution<java.lang.Double> implements Serializable
  - Serialized Fields
    - point
```
double point
```
      Location of the distribution
- Class gov.sandia.cognition.statistics.distribution.DeterministicDistribution.CDF extends DeterministicDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.DeterministicDistribution.PMF extends DeterministicDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.DirichletDistribution extends AbstractDistribution<Vector> implements Serializable
  - Serialized Fields
    - parameters
```
Vector parameters
```
      Parameters of the Dirichlet distribution, must be at least 2-dimensional and each element must be positive.
- Class gov.sandia.cognition.statistics.distribution.DirichletDistribution.PDF extends DirichletDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ExponentialDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - rate
```
double rate
```
      Rate, or inverse scale, of the distribution, must be greater than zero.
- Class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.CDF extends ExponentialDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.PDF extends ExponentialDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ExponentialDistribution.WeightedMaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.GammaDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - shape
```
double shape
```
      Shape parameter of the Gamma distribution, often written as "k", must be greater than zero
    - scale
```
double scale
```
      Scale parameters of the Gamma distribution, often written as "theta", must be greater than zero. Note that this is the INVERSE of what octave uses!!
- Class gov.sandia.cognition.statistics.distribution.GammaDistribution.CDF extends GammaDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.GammaDistribution.MomentMatchingEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.GammaDistribution.PDF extends GammaDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.GammaDistribution.WeightedMomentMatchingEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.GeometricDistribution extends AbstractClosedFormIntegerDistribution implements Serializable
  - Serialized Fields
    - p
```
double p
```
      Probability of a positive outcome (Bernoulli probability), [0,1]
- Class gov.sandia.cognition.statistics.distribution.GeometricDistribution.CDF extends GeometricDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.GeometricDistribution.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.GeometricDistribution.PMF extends GeometricDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - shape
```
double shape
```
      Shape parameter, must be greater than zero.
    - scale
```
double scale
```
      Scale parameter, must be greater than zero.
- Class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution.CDF extends InverseGammaDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.InverseGammaDistribution.PDF extends InverseGammaDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution extends AbstractDistribution<Matrix> implements Serializable
  - Serialized Fields
    - inverseScale
```
Matrix inverseScale
```
      Inverse scale matrix, must be symmetric and positive definite.
    - degreesOfFreedom
```
int degreesOfFreedom
```
      Degrees of freedom, must be greater than the inverse scale dimensionality.
- Class gov.sandia.cognition.statistics.distribution.InverseWishartDistribution.PDF extends InverseWishartDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.KolmogorovDistribution extends AbstractClosedFormUnivariateDistribution<java.lang.Double> implements Serializable
- Class gov.sandia.cognition.statistics.distribution.KolmogorovDistribution.CDF extends KolmogorovDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.LaplaceDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - mean
```
double mean
```
      Mean of the distribution
    - scale
```
double scale
```
      Scale factor of the distribution, must be greater than zero.
- Class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.CDF extends LaplaceDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.PDF extends LaplaceDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.LaplaceDistribution.WeightedMaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.LinearMixtureModel extends AbstractDistribution<DataType> implements Serializable
  - Serialized Fields
    - distributions
```
java.util.ArrayList<E> distributions
```
      Underlying distributions from which we sample
    - priorWeights
```
double[] priorWeights
```
      Weights proportionate by which the distributions are sampled
- Class gov.sandia.cognition.statistics.distribution.LogisticDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - mean
```
double mean
```
      Mean (median and mode) of the distribution.
    - scale
```
double scale
```
      Scale of the distribution, proportionate to the standard deviation, must be greater than zero.
- Class gov.sandia.cognition.statistics.distribution.LogisticDistribution.CDF extends LogisticDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.LogisticDistribution.PDF extends LogisticDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.LogNormalDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - logNormalMean
```
double logNormalMean
```
      Mean of the underlying distribution, (-infinity,+infinity)
    - logNormalVariance
```
double logNormalVariance
```
      Variance of the underlying distribution, (0,infinity)
- Class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.CDF extends LogNormalDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.PDF extends LogNormalDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.LogNormalDistribution.WeightedMaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.EMLearner extends AbstractAnytimeBatchLearner<java.util.Collection<? extends Vector>,MixtureOfGaussians.PDF> implements Serializable
  - Serialized Fields
    - learner
```
MultivariateGaussian.WeightedMaximumLikelihoodEstimator learner
```
      Learner used to estimate each state.
    - random
```
java.util.Random random
```
      Random number generator.
    - tolerance
```
double tolerance
```
      Tolerance before stopping, must be greater than or equal to 0
- Class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.Learner extends AnytimeAlgorithmWrapper<MixtureOfGaussians.PDF,KMeansClusterer<Vector,GaussianCluster>> implements Serializable
- Class gov.sandia.cognition.statistics.distribution.MixtureOfGaussians.PDF extends MultivariateMixtureDensityModel.PDF<MultivariateGaussian> implements Serializable
- Class gov.sandia.cognition.statistics.distribution.MultinomialDistribution extends AbstractDistribution<Vector> implements Serializable
  - Serialized Fields
    - numTrials
```
int numTrials
```
      Number of trials in the distribution, must be greater than 0.
    - parameters
```
Vector parameters
```
      Parameters of the multinomial distribution, must be at least 2-dimensional and each element must be nonnegative.
- Class gov.sandia.cognition.statistics.distribution.MultinomialDistribution.Domain.MultinomialIterator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - value
```
int value
```
      Value at the head of the subset.
    - numClasses
```
int numClasses
```
      Number of classes to sample from.
    - numTrials
```
int numTrials
```
      Number of times to sample from the classes.
    - child
```
MultinomialDistribution.Domain.MultinomialIterator child
```
      Child iterator for recursion.
- Class gov.sandia.cognition.statistics.distribution.MultinomialDistribution.PMF extends MultinomialDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.MultivariateGaussian extends AbstractDistribution<Vector> implements Serializable
  - Serialized Fields
    - mean
```
Vector mean
```
      Mean of the MultivariateGaussian.
    - covariance
```
Matrix covariance
```
      Covariance matrix of the MultivariateGaussian.
    - logCovarianceDeterminant
```
java.lang.Double logCovarianceDeterminant
```
      Natural logarithm of the covariance matrix, automatically computed.
    - covarianceInverse
```
Matrix covarianceInverse
```
      Inverse of the covariance matrix, automatically computed.
    - logLeadingCoefficient
```
java.lang.Double logLeadingCoefficient
```
      Natural logarithm of the leading likelihood coefficient, automatically computed.
- Class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimator extends AbstractIncrementalEstimator<Vector,MultivariateGaussian,MultivariateGaussian.SufficientStatistic> implements Serializable
  - Serialized Fields
    - defaultCovariance
```
double defaultCovariance
```
      Default covariance of the distribution
- Class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimatorCovarianceInverse extends AbstractIncrementalEstimator<Vector,MultivariateGaussian,MultivariateGaussian.SufficientStatisticCovarianceInverse> implements Serializable
  - Serialized Fields
    - defaultCovarianceInverse
```
double defaultCovarianceInverse
```
      Default covariance Inverse of the distribution
- Class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - defaultCovariance
```
double defaultCovariance
```
      Amount to add to the diagonal of the covariance matrix
- Class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.PDF extends MultivariateGaussian implements Serializable
- Class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatistic extends AbstractSufficientStatistic<Vector,MultivariateGaussian> implements Serializable
  - Serialized Fields
    - mean
```
Vector mean
```
      The mean of the Gaussian
    - sumSquaredDifferences
```
Matrix sumSquaredDifferences
```
      This is the sum-squared differences
    - defaultCovariance
```
double defaultCovariance
```
      Default covariance of the distribution
- Class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatisticCovarianceInverse extends AbstractSufficientStatistic<Vector,MultivariateGaussian> implements Serializable
  - Serialized Fields
    - mean
```
Vector mean
```
      The mean of the Gaussian
    - sumSquaredDifferencesInverse
```
Matrix sumSquaredDifferencesInverse
```
      This is the sum-squared differences
    - defaultCovarianceInverse
```
double defaultCovarianceInverse
```
      Default covariance inverse of the distribution
- Class gov.sandia.cognition.statistics.distribution.MultivariateGaussian.WeightedMaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - defaultCovariance
```
double defaultCovariance
```
      Amount to add to the diagonal of the covariance matrix
- Class gov.sandia.cognition.statistics.distribution.MultivariateGaussianInverseGammaDistribution extends AbstractDistribution<Vector> implements Serializable
  - Serialized Fields
    - gaussian
```
MultivariateGaussian gaussian
```
      Gaussian component
    - inverseGamma
```
InverseGammaDistribution inverseGamma
```
      Inverse-Gamma component
- Class gov.sandia.cognition.statistics.distribution.MultivariateMixtureDensityModel extends LinearMixtureModel<Vector,DistributionType extends ClosedFormComputableDistribution<Vector>> implements Serializable
- Class gov.sandia.cognition.statistics.distribution.MultivariateMixtureDensityModel.PDF extends MultivariateMixtureDensityModel<DistributionType extends ClosedFormComputableDistribution<Vector>> implements Serializable
- Class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution extends AbstractDistribution<Vector> implements Serializable
  - Serialized Fields
    - parameters
```
Vector parameters
```
      Parameters of the Dirichlet distribution, must be at least 2-dimensional and each element must be positive.
    - numTrials
```
int numTrials
```
      Number of trials in the distribution, must be greater than 0.
- Class gov.sandia.cognition.statistics.distribution.MultivariatePolyaDistribution.PMF extends MultivariatePolyaDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution extends AbstractDistribution<Vector> implements Serializable
  - Serialized Fields
    - degreesOfFreedom
```
double degreesOfFreedom
```
      Degrees of freedom in the distribution, usually the number of datapoints - 1, DOFs must be greater than zero.
    - mean
```
Vector mean
```
      Mean, or noncentrality parameter, of the distribution
    - precision
```
Matrix precision
```
      Precision, which is proportionate to the inverse of variance, of the distribution, must be symmetric and positive definite.
- Class gov.sandia.cognition.statistics.distribution.MultivariateStudentTDistribution.PDF extends MultivariateStudentTDistribution implements Serializable
  - Serialized Fields
    - logDeterminantPrecision
```
java.lang.Double logDeterminantPrecision
```
      Log determinant of the precision matrix.
- Class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution extends AbstractClosedFormIntegerDistribution implements Serializable
  - Serialized Fields
    - r
```
double r
```
      Number of trials before the experiment is stopped, must be greater than zero.
    - p
```
double p
```
      Probability of a positive outcome (Bernoulli probability), [0,1]
- Class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution.CDF extends NegativeBinomialDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution.PMF extends NegativeBinomialDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.NegativeBinomialDistribution.WeightedMaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution extends AbstractDistribution<Vector> implements Serializable
  - Serialized Fields
    - location
```
double location
```
      Location of the Gaussian kernel.
    - precision
```
double precision
```
      Precision of the Gaussian kernel, must be greater than zero.
    - shape
```
double shape
```
      Shape parameter of the Inverse Gamma kernel, must be greater than zero.
    - scale
```
double scale
```
      Scale parameter of the Inverse Gamma kernel, must be greater than zero.
- Class gov.sandia.cognition.statistics.distribution.NormalInverseGammaDistribution.PDF extends NormalInverseGammaDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution extends AbstractDistribution<Matrix> implements Serializable
  - Serialized Fields
    - covarianceDivisor
```
double covarianceDivisor
```
      Term that divides the covariance sampled from the inverseWishart, must be greater than zero.
    - gaussian
```
MultivariateGaussian gaussian
```
      Generates the mean, given the covariance from the inverseWishart.
    - inverseWishart
```
InverseWishartDistribution inverseWishart
```
      Generates the covariance for the Gaussian.
- Class gov.sandia.cognition.statistics.distribution.NormalInverseWishartDistribution.PDF extends NormalInverseWishartDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ParetoDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - shape
```
double shape
```
      Scale parameter, must be greater than zero.
    - scale
```
double scale
```
      Scale parameter, must be greater than zero.
    - shift
```
double shift
```
      Amount to shift the distribution to the left.
- Class gov.sandia.cognition.statistics.distribution.ParetoDistribution.CDF extends ParetoDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ParetoDistribution.PDF extends ParetoDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.PoissonDistribution extends AbstractClosedFormIntegerDistribution implements Serializable
  - Serialized Fields
    - rate
```
double rate
```
      Expected number of occurrences during the integer interval, must be greater than zero.
- Class gov.sandia.cognition.statistics.distribution.PoissonDistribution.CDF extends PoissonDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.PoissonDistribution.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.PoissonDistribution.PMF extends PoissonDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.PoissonDistribution.WeightedMaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution extends DefaultDataDistribution<java.lang.Double> implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution.CDF extends ScalarDataDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution.Estimator extends AbstractBatchAndIncrementalLearner<java.lang.Double,ScalarDataDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ScalarDataDistribution.PMF extends ScalarDataDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel extends LinearMixtureModel<java.lang.Double,SmoothUnivariateDistribution> implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.CDF extends ScalarMixtureDensityModel implements Serializable
- Class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.EMLearner extends AbstractAnytimeBatchLearner<java.util.Collection<? extends java.lang.Double>,ScalarMixtureDensityModel> implements Serializable
  - Serialized Fields
    - learners
```
java.util.Collection<E> learners
```
      Collection of learners used to create each component.
    - random
```
java.util.Random random
```
      Random number generator.
    - tolerance
```
double tolerance
```
      Tolerance before stopping, must be greater than or equal to 0
- Class gov.sandia.cognition.statistics.distribution.ScalarMixtureDensityModel.PDF extends ScalarMixtureDensityModel implements Serializable
- Class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution extends AbstractClosedFormUnivariateDistribution<java.lang.Double> implements Serializable
  - Serialized Fields
    - v1
```
double v1
```
      First degree of freedom
    - v2
```
double v2
```
      Second degree of freedom
- Class gov.sandia.cognition.statistics.distribution.SnedecorFDistribution.CDF extends SnedecorFDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution extends AbstractClosedFormUnivariateDistribution<java.lang.Double> implements Serializable
  - Serialized Fields
    - treatmentCount
```
int treatmentCount
```
      Number of comparisons made
    - degreesOfFreedom
```
double degreesOfFreedom
```
      Number of subjects in each treatment minus one.
    - random
```
java.util.Random random
```
      Random number generator for Monte Carlo simulations
- Class gov.sandia.cognition.statistics.distribution.StudentizedRangeDistribution.CDF extends StudentizedRangeDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.StudentTDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - precision
```
double precision
```
      Precision, which is proportionate to the inverseRootFinder of variance, of the distribution, must be greater than zero. Note that we are using "precision" instead of "variance" because the variance of the Student-t has another scale factor based on the dofs and we want to avoid confusion.
    - mean
```
double mean
```
      Mean, or noncentrality parameter, of the distribution
    - degreesOfFreedom
```
double degreesOfFreedom
```
      Degrees of freedom in the distribution, usually the number of datapoints - 1, DOFs must be greater than zero.
- Class gov.sandia.cognition.statistics.distribution.StudentTDistribution.CDF extends StudentTDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.StudentTDistribution.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - defaultVariance
```
double defaultVariance
```
      Amount to add to the variance to keep it from being 0.0
- Class gov.sandia.cognition.statistics.distribution.StudentTDistribution.PDF extends StudentTDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.StudentTDistribution.WeightedMaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - defaultVariance
```
double defaultVariance
```
      Amount to add to the variance to keep it from being 0.0
- Class gov.sandia.cognition.statistics.distribution.UniformDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - minSupport
```
double minSupport
```
      Minimum x bound on the distribution
    - maxSupport
```
double maxSupport
```
      Maximum bound on the distribution
- Class gov.sandia.cognition.statistics.distribution.UniformDistribution.CDF extends UniformDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.UniformDistribution.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.UniformDistribution.PDF extends UniformDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution extends AbstractClosedFormIntegerDistribution implements Serializable
  - Serialized Fields
    - minSupport
```
int minSupport
```
      The minimum bound on the distribution (inclusive).
    - maxSupport
```
int maxSupport
```
      The maximum bound on the distribution (inclusive).
- Class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution.CDF extends UniformIntegerDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.distribution.UniformIntegerDistribution.PMF extends UniformIntegerDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.UnivariateGaussian extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - mean
```
double mean
```
      First central moment (expectation) of the distribution
    - variance
```
double variance
```
      Second central moment (square of standard deviation) of the distribution
- Class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.CDF extends UnivariateGaussian implements Serializable
- Class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.CDF.Inverse extends UnivariateGaussian implements Serializable
- Class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.ErrorFunction extends AbstractUnivariateScalarFunction implements Serializable
- Class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.ErrorFunction.Inverse extends AbstractUnivariateScalarFunction implements Serializable
- Class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.IncrementalEstimator extends AbstractIncrementalEstimator<java.lang.Double,UnivariateGaussian,UnivariateGaussian.SufficientStatistic> implements Serializable
  - Serialized Fields
    - defaultVariance
```
double defaultVariance
```
      Amount to add to the variance to keep it from being 0.0.
- Class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - defaultVariance
```
double defaultVariance
```
      Amount to add to the variance to keep it from being 0.0
- Class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.PDF extends UnivariateGaussian implements Serializable
- Class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.SufficientStatistic extends AbstractSufficientStatistic<java.lang.Double,UnivariateGaussian> implements Serializable
  - Serialized Fields
    - mean
```
double mean
```
      The mean of the Gaussian.
    - sumSquaredDifferences
```
double sumSquaredDifferences
```
      This is the sum-squared differences
- Class gov.sandia.cognition.statistics.distribution.UnivariateGaussian.WeightedMaximumLikelihoodEstimator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - defaultVariance
```
double defaultVariance
```
      Amount to add to the variance to keep it from being 0.0
- Class gov.sandia.cognition.statistics.distribution.WeibullDistribution extends AbstractClosedFormSmoothUnivariateDistribution implements Serializable
  - Serialized Fields
    - shape
```
double shape
```
      Shape parameter, must be greater than 0.0
    - scale
```
double scale
```
      Scale parameter, must be greater than 0.0
- Class gov.sandia.cognition.statistics.distribution.WeibullDistribution.CDF extends WeibullDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.WeibullDistribution.PDF extends WeibullDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution extends AbstractClosedFormIntegerDistribution implements Serializable
  - Serialized Fields
    - shape
```
double shape
```
      Shape parameter, must be greater than zero
- Class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution.CDF extends YuleSimonDistribution implements Serializable
- Class gov.sandia.cognition.statistics.distribution.YuleSimonDistribution.PMF extends YuleSimonDistribution implements Serializable
Package gov.sandia.cognition.statistics.method
- Class gov.sandia.cognition.statistics.method.AbstractConfidenceStatistic extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - nullHypothesisProbability
```
double nullHypothesisProbability
```
      Probability of the null hypothesis, often called "p-value"
- Class gov.sandia.cognition.statistics.method.AbstractMultipleHypothesisComparison extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.AbstractMultipleHypothesisComparison.Statistic extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - treatmentCount
```
int treatmentCount
```
      Number of treatments being compared
    - uncompensatedAlpha
```
double uncompensatedAlpha
```
      Uncompensated alpha (p-value threshold) for the multiple comparison test
    - testStatistics
```
Matrix testStatistics
```
      Test statistic associated with the (i,j) treatment comparison
    - nullHypothesisProbabilities
```
Matrix nullHypothesisProbabilities
```
      Null Hypothesis probability associated with the (i,j) treatment comparison
- Class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison extends AbstractMultipleHypothesisComparison<java.util.Collection<? extends java.lang.Number>,StatisticType extends AbstractPairwiseMultipleHypothesisComparison.Statistic> implements Serializable
  - Serialized Fields
    - pairwiseTest
```
NullHypothesisEvaluator<DataType> pairwiseTest
```
      Confidence test used for pair-wise null-hypothesis tests.
- Class gov.sandia.cognition.statistics.method.AbstractPairwiseMultipleHypothesisComparison.Statistic extends AbstractMultipleHypothesisComparison.Statistic implements Serializable
  - Serialized Fields
    - pairwiseTestStatistics
```
java.util.ArrayList<E> pairwiseTestStatistics
```
      Results from the pair-wise confidence tests.
- Class gov.sandia.cognition.statistics.method.AdjustedPValueStatistic extends AbstractPairwiseMultipleHypothesisComparison.Statistic implements Serializable
  - Serialized Fields
    - adjustedAlpha
```
double adjustedAlpha
```
      Adjusted alpha term to account for multiple comparisons
- Class gov.sandia.cognition.statistics.method.AnalysisOfVarianceOneWay extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.AnalysisOfVarianceOneWay.Statistic extends AbstractConfidenceStatistic implements Serializable
  - Serialized Fields
    - F
```
double F
```
      Input to the Snedecor F-distribution
    - DFbetween
```
double DFbetween
```
      Degrees of freedom between the treatments
    - DFwithin
```
double DFwithin
```
      Degrees of freedom within the treatments
- Class gov.sandia.cognition.statistics.method.BernoulliConfidence extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.BonferroniCorrection extends AbstractPairwiseMultipleHypothesisComparison<AdjustedPValueStatistic> implements Serializable
- Class gov.sandia.cognition.statistics.method.ChebyshevInequality extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.ChiSquareConfidence extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.ChiSquareConfidence.Statistic extends AbstractConfidenceStatistic implements Serializable
  - Serialized Fields
    - chiSquare
```
double chiSquare
```
      Chi-square value
    - degreesOfFreedom
```
double degreesOfFreedom
```
      Number of degrees of freedom in the test
- Class gov.sandia.cognition.statistics.method.ConfidenceInterval extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - lowerBound
```
double lowerBound
```
      Lower bound for the statistic
    - upperBound
```
double upperBound
```
      Upper bound for the statistic
    - centralValue
```
double centralValue
```
      Central value of the statistic (expectation, maximum likelihood, etc.)
    - confidence
```
double confidence
```
      Confidence that the statistic is within the bound, or 1-alpha, on the interval [0,1], where confidence=0 means definitely not within the bound and confidence=1 means definite within the bound.
    - numSamples
```
int numSamples
```
      Number of sample values used to create the interval
- Class gov.sandia.cognition.statistics.method.ConvexReceiverOperatingCharacteristic extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - convexHull
```
java.util.ArrayList<E> convexHull
```
      Convex hull of the ROC curve
- Class gov.sandia.cognition.statistics.method.DistributionParameterEstimator extends AnytimeAlgorithmWrapper<DistributionType extends ClosedFormDistribution<? extends DataType>,FunctionMinimizer<Vector,java.lang.Double,? super DistributionParameterEstimator.DistributionWrapper>> implements Serializable
  - Serialized Fields
    - distributionWrapper
```
DistributionParameterEstimator.DistributionWrapper distributionWrapper
```
      Function that maps a Distribution onto a Vector/Scalar function.
    - result
```
ClosedFormDistribution<DataType> result
```
      Distribution that minimizes the cost function.
- Class gov.sandia.cognition.statistics.method.DistributionParameterEstimator.DistributionWrapper extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - distribution
```
ClosedFormDistribution<DataType> distribution
```
      Distribution to estimate the parameters of
    - costFunction
```
CostFunction<EvaluatedType,CostParametersType> costFunction
```
      Cost function to use in the minimization procedure
- Class gov.sandia.cognition.statistics.method.FieldConfidenceInterval extends ConfidenceInterval implements Serializable
  - Serialized Fields
    - field
```
java.lang.reflect.Field field
```
      Field associated with the confidence interval
- Class gov.sandia.cognition.statistics.method.FisherSignConfidence extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.FisherSignConfidence.Statistic extends AbstractConfidenceStatistic implements Serializable
  - Serialized Fields
    - numDifferent
```
int numDifferent
```
      Number of samples where data1 was different than data2
    - numPositiveSign
```
int numPositiveSign
```
      Number of sample where data1 was greater than data2
- Class gov.sandia.cognition.statistics.method.FriedmanConfidence extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.FriedmanConfidence.Statistic extends AbstractConfidenceStatistic implements Serializable
  - Serialized Fields
    - treatmentCount
```
int treatmentCount
```
      Number of treatments in the experiment
    - subjectCount
```
int subjectCount
```
      Number of subjects in the experiment
    - chiSquare
```
double chiSquare
```
      Value of the chi-square error for the treatment ranks
    - degreesOfFreedom
```
double degreesOfFreedom
```
      Degrees of freedom of the chi-square
    - chiSquareNullHypothesisProbability
```
double chiSquareNullHypothesisProbability
```
      Null-hypothesis using the chi-square statistic
    - F
```
double F
```
      F-statistic for the corrected chi-square using Snedecor's F distribution
    - treatmentRankMeans
```
java.util.ArrayList<E> treatmentRankMeans
```
      Mean rank for each treatment
- Class gov.sandia.cognition.statistics.method.GaussianConfidence extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.GaussianConfidence.Statistic extends AbstractConfidenceStatistic implements Serializable
  - Serialized Fields
    - z
```
double z
```
      Value that is used in the Gaussian CDF to compute probability. Usually just called "z-statistic"
- Class gov.sandia.cognition.statistics.method.HolmCorrection extends AbstractPairwiseMultipleHypothesisComparison<HolmCorrection.Statistic> implements Serializable
- Class gov.sandia.cognition.statistics.method.HolmCorrection.Statistic extends AbstractPairwiseMultipleHypothesisComparison.Statistic implements Serializable
  - Serialized Fields
    - adjustedAlphas
```
Matrix adjustedAlphas
```
      Matrix of adjusted alphas (p-value thresholds) for each comparison
- Class gov.sandia.cognition.statistics.method.KolmogorovSmirnovConfidence extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.KolmogorovSmirnovConfidence.Statistic extends AbstractConfidenceStatistic implements Serializable
  - Serialized Fields
    - D
```
double D
```
      This is the D-statistic used in the K-S CDF, usually known as the D-statistic, which is the maximum difference between the two distributions. I use the two-tail version of D.
    - Ne
```
double Ne
```
      This is the degrees of freedom in the K-S distribution for the CDF calculation.
- Class gov.sandia.cognition.statistics.method.MannWhitneyUConfidence extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.MannWhitneyUConfidence.Statistic extends AbstractConfidenceStatistic implements Serializable
  - Serialized Fields
    - U
```
double U
```
      U statistic, minimum rank sum above "chance"
    - z
```
double z
```
      z-value for a UnivariateGaussian CDF, number of standard deviations away from chance
    - N1
```
int N1
```
      Number of samples in data1
    - N2
```
int N2
```
      Number of samples in data2
- Class gov.sandia.cognition.statistics.method.MarkovInequality extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.MaximumLikelihoodDistributionEstimator extends AbstractParallelAlgorithm implements Serializable
  - Serialized Fields
    - distributions
```
java.util.Collection<E> distributions
```
      Collection of Distributions to estimate the optimal parameters of
- Class gov.sandia.cognition.statistics.method.MaximumLikelihoodDistributionEstimator.DistributionEstimationTask extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - distribution
```
ClosedFormComputableDistribution<DataType> distribution
```
      Distribution to estimate
    - data
```
java.util.Collection<E> data
```
      Data to use in the estimation
- Class gov.sandia.cognition.statistics.method.MultipleComparisonExperiment extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - blockExperimentComparison
```
BlockExperimentComparison<DataType> blockExperimentComparison
```
      Block-experiment comparison test that determines if there is a statistically significant difference in one of the treatments
    - postHocTest
```
MultipleHypothesisComparison<TreatmentData> postHocTest
```
      Post-hoc test that determines which treatments are statistically significantly different
    - alpha
```
double alpha
```
      P-value threshold, such that if the null-hypothesis probability is below alpha then we reject the null hypothesis.
- Class gov.sandia.cognition.statistics.method.MultipleComparisonExperiment.Statistic extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - blockExperimentResult
```
ConfidenceStatistic blockExperimentResult
```
      Result from the block-experiment null-hypothesis test
    - multipleComparisonResult
```
MultipleHypothesisComparison.Statistic multipleComparisonResult
```
      Result from the multiple hypothesis comparison null-hypothesis test, which will exist if the block-experiment null hypothesis is rejected
- Class gov.sandia.cognition.statistics.method.NemenyiConfidence extends AbstractMultipleHypothesisComparison<java.util.Collection<? extends java.lang.Number>,NemenyiConfidence.Statistic> implements Serializable
- Class gov.sandia.cognition.statistics.method.NemenyiConfidence.Statistic extends AbstractMultipleHypothesisComparison.Statistic implements Serializable
  - Serialized Fields
    - subjectCount
```
int subjectCount
```
      Number of subjects in each treatment
    - treatmentRankMeans
```
java.util.ArrayList<E> treatmentRankMeans
```
      Mean for each treatment
    - standardError
```
double standardError
```
      Standard error of the entire experiment
- Class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - sortedROCData
```
java.util.ArrayList<E> sortedROCData
```
      Sorted data containing a ConfusionMatrix at each point, sorted in an ascending order along the abscissa (x-axis), which is FalsePositiveRate
    - Utest
```
MannWhitneyUConfidence.Statistic Utest
```
      Results from conducting a U-test on the underlying classification data, the null hypothesis determines if the classifier can reliably separate the classes, not just chance
- Class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.DataPoint extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - classifier
```
ScalarThresholdBinaryCategorizer classifier
```
      Binary classifier used to create the corresponding ConfusionMatrix, which is really a wrapper for the threshold
    - confusionMatrix
```
DefaultBinaryConfusionMatrix confusionMatrix
```
      Corresponding ConfusionMatrix with this datapoint
- Class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.DataPoint.Sorter extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic.Statistic extends MannWhitneyUConfidence.Statistic implements Serializable
  - Serialized Fields
    - dPrime
```
double dPrime
```
      Estimated distance between the two classes to be split. Larger values of d' indicate that the classes are easier to split, d'=0 means that the classes overlap, and negative values mean that your classifier is doing worse than chance, chump. This appears to only be used by psychologists.
    - areaUnderCurve
```
double areaUnderCurve
```
      Area underneath the ROC curve, on the interval [0,1]. A value of 0.5 means that the classifier is doing no better than chance and bigger is better
    - optimalThreshold
```
ReceiverOperatingCharacteristic.DataPoint optimalThreshold
```
      DataPoint, with corresponding threshold, that maximizes the value of Area=TruePositiveRate*(1-FalsePositiveRate), usually the upper-left "knee" on the ROC curve
- Class gov.sandia.cognition.statistics.method.ShafferStaticCorrection extends AbstractPairwiseMultipleHypothesisComparison<ShafferStaticCorrection.Statistic> implements Serializable
- Class gov.sandia.cognition.statistics.method.ShafferStaticCorrection.Statistic extends AbstractPairwiseMultipleHypothesisComparison.Statistic implements Serializable
  - Serialized Fields
    - adjustedAlphas
```
Matrix adjustedAlphas
```
      Matrix of adjusted alphas (p-value thresholds) for each comparison
- Class gov.sandia.cognition.statistics.method.SidakCorrection extends AbstractPairwiseMultipleHypothesisComparison<AdjustedPValueStatistic> implements Serializable
- Class gov.sandia.cognition.statistics.method.StudentTConfidence extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.StudentTConfidence.Statistic extends AbstractConfidenceStatistic implements Serializable
  - Serialized Fields
    - t
```
double t
```
      Value that is used in the Student-t CDF to compute the probability. Usually just called the "t-statistic"
    - degreesOfFreedom
```
double degreesOfFreedom
```
      Number of degrees of freedom in the Student-t distribution, usually the number of data points - 1
- Class gov.sandia.cognition.statistics.method.StudentTConfidence.Summary extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - confidence
```
double confidence
```
      The confidence for the created interval.
- Class gov.sandia.cognition.statistics.method.TreeSetBinner extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - binSet
```
java.util.TreeSet<E> binSet
```
      TreeSet used to store bin boundaries, determine which bin a value goes in.
    - minValue
```
java.lang.Comparable<T> minValue
```
      Minimum value, inclusive, allowed in bins.
    - maxValue
```
java.lang.Comparable<T> maxValue
```
      Maximum value, exclusive, allowed in bins.
- Class gov.sandia.cognition.statistics.method.TukeyKramerConfidence extends AbstractMultipleHypothesisComparison<java.util.Collection<? extends java.lang.Number>,TukeyKramerConfidence.Statistic> implements Serializable
- Class gov.sandia.cognition.statistics.method.TukeyKramerConfidence.Statistic extends AbstractMultipleHypothesisComparison.Statistic implements Serializable
  - Serialized Fields
    - subjectCounts
```
java.util.ArrayList<E> subjectCounts
```
      Number of subjects in each treatment
    - treatmentMeans
```
java.util.ArrayList<E> treatmentMeans
```
      Mean for each treatment
    - meanSquaredResiduals
```
double meanSquaredResiduals
```
      Mean-squared difference over all subjects
    - standardErrors
```
Matrix standardErrors
```
      Gets the standard errors in the experiment
- Class gov.sandia.cognition.statistics.method.WilcoxonSignedRankConfidence extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.method.WilcoxonSignedRankConfidence.Statistic extends AbstractConfidenceStatistic implements Serializable
  - Serialized Fields
    - T
```
double T
```
      Wilcoxon T statistic, minimum sign-rank sum
    - numNonZero
```
int numNonZero
```
      Number of nonzero differences in the data
    - z
```
double z
```
      Z-statistic for the Gaussian CDF
Package gov.sandia.cognition.statistics.montecarlo
- Class gov.sandia.cognition.statistics.montecarlo.DirectSampler extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.montecarlo.ImportanceSampler extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - importanceDistribution
```
ProbabilityFunction<DataType> importanceDistribution
```
      Importance distribution from which we sample and weight by the target distribution.
- Class gov.sandia.cognition.statistics.montecarlo.MultivariateMonteCarloIntegrator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.statistics.montecarlo.UnivariateMonteCarloIntegrator extends AbstractCloneableSerializable implements Serializable
Package gov.sandia.cognition.text
- Class gov.sandia.cognition.text.AbstractOccurrenceInText extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - start
```
int start
```
      The starting point of the occurrence.
    - length
```
int length
```
      The length of the occurrence.
- Class gov.sandia.cognition.text.AbstractTextual extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.text.DefaultTextual extends AbstractTextual implements Serializable
  - Serialized Fields
    - text
```
java.lang.String text
```
      The text value.
Package gov.sandia.cognition.text.convert
- Class gov.sandia.cognition.text.convert.AbstractMultiTextualConverter extends AbstractTextualConverter<InputType,OutputType extends Textual> implements Serializable
- Class gov.sandia.cognition.text.convert.AbstractSingleTextualConverter extends AbstractDataConverter<InputType,OutputType extends Textual> implements Serializable
- Class gov.sandia.cognition.text.convert.AbstractTextualConverter extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.text.convert.DocumentFieldConcatenator extends AbstractSingleTextualConverter<Document,Textual> implements Serializable
  - Serialized Fields
    - fieldNames
```
java.util.List<E> fieldNames
```
      The list of fields to concatenate together from a document.
    - fieldSeparator
```
java.lang.String fieldSeparator
```
      The field separator.
- Class gov.sandia.cognition.text.convert.DocumentSingleFieldConverter extends AbstractSingleTextualConverter<Document,Field> implements Serializable
  - Serialized Fields
    - fieldName
```
java.lang.String fieldName
```
      The name of the field to extract.
- Class gov.sandia.cognition.text.convert.ObjectToStringTextualConverter extends AbstractSingleTextualConverter<java.lang.Object,DefaultTextual> implements Serializable
- Class gov.sandia.cognition.text.convert.SingleToMultiTextualConverterAdapter extends AbstractMultiTextualConverter<InputType,OutputType extends Textual> implements Serializable
  - Serialized Fields
    - converter
```
SingleTextualConverter<InputType,OutputType extends Textual> converter
```
      The single text converter being wrapped.
Package gov.sandia.cognition.text.document
- Class gov.sandia.cognition.text.document.AbstractDocument extends AbstractNamed implements Serializable
  - Serialized Fields
    - reference
```
DocumentReference reference
```
      A reference to where the document came from.
    - fieldMap
```
java.util.HashMap<K,V> fieldMap
```
      A mapping of field names to fields.
- Class gov.sandia.cognition.text.document.AbstractField extends AbstractNamed implements Serializable
- Class gov.sandia.cognition.text.document.DefaultDateField extends AbstractField implements Serializable
  - Serialized Fields
    - date
```
java.util.Date date
```
      The date stored in the field.
- Class gov.sandia.cognition.text.document.DefaultDocument extends AbstractDocument implements Serializable
- Class gov.sandia.cognition.text.document.DefaultTextField extends AbstractField implements Serializable
  - Serialized Fields
    - text
```
java.lang.String text
```
      The text content of the field.
Package gov.sandia.cognition.text.document.extractor
- Class gov.sandia.cognition.text.document.extractor.AbstractDocumentExtractor extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.text.document.extractor.AbstractSingleDocumentExtractor extends AbstractDocumentExtractor implements Serializable
- Class gov.sandia.cognition.text.document.extractor.DocumentExtractionException extends java.lang.Exception implements Serializable
- Class gov.sandia.cognition.text.document.extractor.TextDocumentExtractor extends AbstractSingleDocumentExtractor implements Serializable
Package gov.sandia.cognition.text.evaluation
- Class gov.sandia.cognition.text.evaluation.DefaultPrecisionRecallPair extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - precision
```
double precision
```
      The precision value.
    - recall
```
double recall
```
      The recall value.
Package gov.sandia.cognition.text.relation
- Class gov.sandia.cognition.text.relation.AbstractRelation extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - source
```
java.lang.Object source
```
      The source object of the relation.
    - target
```
java.lang.Object target
```
      The target object of the relation.
Package gov.sandia.cognition.text.spelling
- Class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - wordCounts
```
DefaultDataDistribution<KeyType> wordCounts
```
      Maps known words to the number of times they've been seen.
    - alphabet
```
char[] alphabet
```
      The alphabet of lower case characters.
- Class gov.sandia.cognition.text.spelling.SimpleStatisticalSpellingCorrector.Learner extends AbstractBatchAndIncrementalLearner<java.lang.String,SimpleStatisticalSpellingCorrector> implements Serializable
  - Serialized Fields
    - alphabet
```
char[] alphabet
```
      The alphabet of lower case characters.
Package gov.sandia.cognition.text.term
- Class gov.sandia.cognition.text.term.AbstractTerm extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.text.term.AbstractTermIndex extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.text.term.DefaultIndexedTerm extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - index
```
int index
```
      The index of the term.
    - term
```
Term term
```
      The term.
- Class gov.sandia.cognition.text.term.DefaultTerm extends AbstractTerm implements Serializable
  - Serialized Fields
    - text
```
java.lang.String text
```
      The text of the term.
- Class gov.sandia.cognition.text.term.DefaultTermCounts extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - totalCount
```
int totalCount
```
      The total of all counts.
    - termToCountMap
```
java.util.HashMap<K,V> termToCountMap
```
      The mapping of terms to their respective counts.
- Class gov.sandia.cognition.text.term.DefaultTermIndex extends AbstractTermIndex implements Serializable
  - Serialized Fields
    - termMap
```
java.util.Map<K,V> termMap
```
      The mapping of terms to their corresponding (unique) indices.
    - termList
```
java.util.List<E> termList
```
      The list of terms ordered by indices.
- Class gov.sandia.cognition.text.term.DefaultTermNGram extends AbstractTerm implements Serializable
  - Serialized Fields
    - terms
```
Term[] terms
```
      The array of terms that make up the n-gram.
- Class gov.sandia.cognition.text.term.DefaultTermOccurrence extends AbstractOccurrenceInText<Term> implements Serializable
  - Serialized Fields
    - term
```
Term term
```
      The term that occurred.
Package gov.sandia.cognition.text.term.filter
- Class gov.sandia.cognition.text.term.filter.AbstractSingleTermFilter extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.text.term.filter.DefaultStopList extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - words
```
java.util.Set<E> words
```
      The set of words in the stop list, all in lower-case.
- Class gov.sandia.cognition.text.term.filter.DictionaryFilter extends AbstractSingleTermFilter implements Serializable
  - Serialized Fields
    - allowedTerms
```
java.util.Set<E> allowedTerms
```
      The set of terms allowed by the filter. All other terms are discarded.
- Class gov.sandia.cognition.text.term.filter.LowerCaseTermFilter extends AbstractSingleTermFilter implements Serializable
- Class gov.sandia.cognition.text.term.filter.NGramFilter extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - size
```
int size
```
      The size of the n-gram. Also known as the value of n.
- Class gov.sandia.cognition.text.term.filter.StopListFilter extends AbstractSingleTermFilter implements Serializable
  - Serialized Fields
    - stopList
```
StopList stopList
```
      The stop list for the filter to use.
- Class gov.sandia.cognition.text.term.filter.StringEvaluatorSingleTermFilter extends AbstractSingleTermFilter implements Serializable
  - Serialized Fields
    - evaluator
```
Evaluator<InputType,OutputType> evaluator
```
      The evaluator to adapt.
- Class gov.sandia.cognition.text.term.filter.SynonymFilter extends AbstractSingleTermFilter implements Serializable
  - Serialized Fields
    - synonyms
```
java.util.Map<K,V> synonyms
```
      The mapping of terms to the synonym to replace them with.
- Class gov.sandia.cognition.text.term.filter.TermLengthFilter extends AbstractSingleTermFilter implements Serializable
  - Serialized Fields
    - minimumLength
```
java.lang.Integer minimumLength
```
      The minimum allowed length. Inclusive. A null value indicates no minimum. Must be non-negative.
    - maximumLength
```
java.lang.Integer maximumLength
```
      The maximum allowed length. Inclusive. A null value indicates no maximum. Must be non-negative.
Package gov.sandia.cognition.text.term.filter.stem
- Class gov.sandia.cognition.text.term.filter.stem.PorterEnglishStemmingFilter extends AbstractSingleTermFilter implements Serializable
Package gov.sandia.cognition.text.term.relation
- Class gov.sandia.cognition.text.term.relation.IndexedTermSimilarityRelation extends AbstractRelation<IndexedTerm,IndexedTerm> implements Serializable
  - Serialized Fields
    - similarity
```
double similarity
```
      The similarity between the two terms.
- Class gov.sandia.cognition.text.term.relation.TermVectorSimilarityNetworkCreator extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - similarityFunction
```
SimilarityFunction<FromType,ToType> similarityFunction
```
      The similarity function between term vectors used to determine the similarity between two terms.
    - effectiveZero
```
double effectiveZero
```
      The value to treat as zero. Used to increase the sparseness of a similarity network.
    - matrixFactory
```
MatrixFactory<MatrixType extends Matrix> matrixFactory
```
      The matrix factory to create the matrix that backs the similarity network.
Package gov.sandia.cognition.text.term.vector
- Class gov.sandia.cognition.text.term.vector.AbstractVectorSpaceModel extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.text.term.vector.BagOfWordsTransform extends DefaultVectorFactoryContainer implements Serializable
  - Serialized Fields
    - termIndex
```
TermIndex termIndex
```
      Gets the term index used by the transform. Maps terms to indices in the vector.
- Class gov.sandia.cognition.text.term.vector.CosineSimilarityFunction extends AbstractCloneableSerializable implements Serializable
Package gov.sandia.cognition.text.term.vector.weighter
- Class gov.sandia.cognition.text.term.vector.weighter.CompositeLocalGlobalTermWeighter extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - localWeighter
```
LocalTermWeighter localWeighter
```
      The weighting scheme for the local weights. Null means no local weights.
    - globalWeighter
```
GlobalTermWeighter globalWeighter
```
      The weighting scheme for the global weights. Null means no global weights.
    - normalizer
```
TermWeightNormalizer normalizer
```
      The weight normalizer.
Package gov.sandia.cognition.text.term.vector.weighter.global
- Class gov.sandia.cognition.text.term.vector.weighter.global.AbstractEntropyBasedGlobalTermWeighter extends AbstractFrequencyBasedGlobalTermWeighter implements Serializable
  - Serialized Fields
    - termEntropiesSum
```
Vector termEntropiesSum
```
      A vector containing the sum of the entropy term (f_ij * log(f_ij)) over each document in the collection for each term.
- Class gov.sandia.cognition.text.term.vector.weighter.global.AbstractFrequencyBasedGlobalTermWeighter extends AbstractGlobalTermWeighter implements Serializable
  - Serialized Fields
    - documentCount
```
int documentCount
```
      The number of documents the weight is computed over.
    - termDocumentFrequencies
```
Vector termDocumentFrequencies
```
      The vector containing the number of documents that each term occurs in.
    - termGlobalFrequencies
```
Vector termGlobalFrequencies
```
      A vector containing the total number of times that each term occurred in the document set.
- Class gov.sandia.cognition.text.term.vector.weighter.global.AbstractGlobalTermWeighter extends AbstractVectorSpaceModel implements Serializable
  - Serialized Fields
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The vector factory.
- Class gov.sandia.cognition.text.term.vector.weighter.global.DominanceGlobalTermWeighter extends AbstractEntropyBasedGlobalTermWeighter implements Serializable
  - Serialized Fields
    - dominance
```
Vector dominance
```
      A vector caching the global dominance weight of the document collection. It may be null. Use getDominance() to compute the proper value if it has not been updated yet.
- Class gov.sandia.cognition.text.term.vector.weighter.global.EntropyGlobalTermWeighter extends AbstractEntropyBasedGlobalTermWeighter implements Serializable
  - Serialized Fields
    - entropy
```
Vector entropy
```
      A vector caching the global entropy weight of the document collection. It may be null. Use getEntropy() to compute the proper value if it has not been updated yet.
- Class gov.sandia.cognition.text.term.vector.weighter.global.InverseDocumentFrequencyGlobalTermWeighter extends AbstractFrequencyBasedGlobalTermWeighter implements Serializable
  - Serialized Fields
    - inverseDocumentFrequency
```
Vector inverseDocumentFrequency
```
      The (cached) value of the inverse document frequency. The cached value is cleared out whenever a document is added or removed. It is recomputed from the other state values on request.
Package gov.sandia.cognition.text.term.vector.weighter.local
- Class gov.sandia.cognition.text.term.vector.weighter.local.AbstractLocalTermWeighter extends DefaultVectorFactoryContainer implements Serializable
- Class gov.sandia.cognition.text.term.vector.weighter.local.BinaryLocalTermWeighter extends AbstractLocalTermWeighter implements Serializable
- Class gov.sandia.cognition.text.term.vector.weighter.local.LogLocalTermWeighter extends AbstractLocalTermWeighter implements Serializable
- Class gov.sandia.cognition.text.term.vector.weighter.local.NormalizedLogLocalTermWeighter extends LogLocalTermWeighter implements Serializable
- Class gov.sandia.cognition.text.term.vector.weighter.local.TermFrequencyLocalTermWeighter extends AbstractLocalTermWeighter implements Serializable
Package gov.sandia.cognition.text.term.vector.weighter.normalize
- Class gov.sandia.cognition.text.term.vector.weighter.normalize.AbstractTermWeightNormalizer extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.text.term.vector.weighter.normalize.UnitTermWeightNormalizer extends AbstractTermWeightNormalizer implements Serializable
Package gov.sandia.cognition.text.token
- Class gov.sandia.cognition.text.token.AbstractCharacterBasedTokenizer extends AbstractTokenizer implements Serializable
- Class gov.sandia.cognition.text.token.AbstractTokenizer extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.text.token.DefaultToken extends AbstractOccurrenceInText<Term> implements Serializable
  - Serialized Fields
    - text
```
java.lang.String text
```
      The text of the token.
- Class gov.sandia.cognition.text.token.LetterNumberTokenizer extends AbstractCharacterBasedTokenizer implements Serializable
Package gov.sandia.cognition.text.topic
- Class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler extends AbstractAnytimeBatchLearner<java.util.Collection<? extends Vectorizable>,LatentDirichletAllocationVectorGibbsSampler.Result> implements Serializable
  - Serialized Fields
    - topicCount
```
int topicCount
```
      The number of topics for the algorithm to create.
    - alpha
```
double alpha
```
      The alpha parameter controlling the Dirichlet distribution for the document-topic probabilities. It acts as a prior weight assigned to the document-topic counts.
    - beta
```
double beta
```
      The beta parameter controlling the Dirichlet distribution for the topic-term probabilities. It acts as a prior weight assigned to the topic-term counts.
    - burnInIterations
```
int burnInIterations
```
      The number of burn-in iterations for the Markov Chain Monte Carlo algorithm to run before sampling begins.
    - iterationsPerSample
```
int iterationsPerSample
```
      The number of iterations to the Markov Chain Monte Carlo algorithm between samples (after the burn-in iterations).
    - random
```
java.util.Random random
```
      The random number generator to use.
- Class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler.Result extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - topicTermProbabilities
```
double[][] topicTermProbabilities
```
      The topic-term probabilities, which are the often called the phi model parameters. Note that if multiple samples are taken, this will be a sum of the probabilities for the different samples until the algorithm is done and they are turned into an average.
    - documentTopicProbabilities
```
double[][] documentTopicProbabilities
```
      The document-topic probabilities, which are often called the theta model parameters. Note that if multiple samples are taken, this will be a sum of the probabilities for the different samples until the algorithm is done and they are turned into an average.
    - totalOccurrences
```
int totalOccurrences
```
      The total number for term occurrences
- Class gov.sandia.cognition.text.topic.LatentSemanticAnalysis extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - requestedRank
```
int requestedRank
```
      The rank requested for the result LSA. The results may have smaller rank if the requested rank is greater than the number of documents. Must be positive.
- Class gov.sandia.cognition.text.topic.LatentSemanticAnalysis.Transform extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - termBasis
```
Matrix termBasis
```
      The matrix of orthogonal term column vectors.
    - singularValues
```
Matrix singularValues
```
      The diagonal matrix of singular values.
    - transform
```
Matrix transform
```
      The cached transform matrix. It is the term basis times the singular values.
- Class gov.sandia.cognition.text.topic.ParallelLatentDirichletAllocationVectorGibbsSampler extends LatentDirichletAllocationVectorGibbsSampler implements Serializable
- Class gov.sandia.cognition.text.topic.ParallelLatentDirichletAllocationVectorGibbsSampler.DocumentSampleTask extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - vector
```
Vector vector
```
      The term vector for a document.
    - document
```
int document
```
      The document address
    - occurrence
```
int occurrence
```
      The occurrence address
- Class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis extends AbstractAnytimeBatchLearner<java.util.Collection<? extends Vectorizable>,ProbabilisticLatentSemanticAnalysis.Result> implements Serializable
  - Serialized Fields
    - requestedRank
```
int requestedRank
```
      The requested rank to reduce the dimensionality to.
    - minimumChange
```
double minimumChange
```
      The minimum change required in log-likelihood to continue iterating. Used for a stopping criteria.
    - random
```
java.util.Random random
```
      The random number generator to use.
    - vectorFactory
```
VectorFactory<VectorType extends Vector> vectorFactory
```
      The vector factory.
    - matrixFactory
```
MatrixFactory<MatrixType extends Matrix> matrixFactory
```
      The matrix factory.
- Class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis.Result extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - termCount
```
int termCount
```
      The number of terms.
    - latentCount
```
int latentCount
```
      The number of latent variables.
    - latents
```
ProbabilisticLatentSemanticAnalysis.LatentData[] latents
```
      The latent variable data.
    - maxIterations
```
int maxIterations
```
      The maximum number of iterations for the E-M evaluation.
    - minimumChange
```
double minimumChange
```
      The minimum change in log-likelihood for the E-M evaluation.
- Class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis.StatusPrinter extends AbstractIterativeAlgorithmListener implements Serializable
  - Serialized Fields
    - out
```
java.io.PrintStream out
```
      The stream to write the status to.
Package gov.sandia.cognition.time
- Class gov.sandia.cognition.time.DefaultDuration extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - milliseconds
```
double milliseconds
```
      The default duration keeps track of milliseconds.
Package gov.sandia.cognition.util
- Class gov.sandia.cognition.util.AbstractCloneableSerializable extends java.lang.Object implements Serializable
- Class gov.sandia.cognition.util.AbstractNamed extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - name
```
java.lang.String name
```
      The name of the object.
- Class gov.sandia.cognition.util.AbstractRandomized extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - random
```
java.util.Random random
```
      The random number generator for this object to use.
- Class gov.sandia.cognition.util.AbstractTemporal extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - time
```
java.util.Date time
```
      Time associated with the value
- Class gov.sandia.cognition.util.AbstractWeighted extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - weight
```
double weight
```
      The weight
- Class gov.sandia.cognition.util.DefaultIdentifiedValue extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - identifier
```
java.lang.Object identifier
```
      The identifier for the value.
    - value
```
java.lang.Object value
```
      The value.
- Class gov.sandia.cognition.util.DefaultKeyValuePair extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - key
```
java.lang.Object key
```
      The key part in the pair, which is the first element.
    - value
```
java.lang.Object value
```
      The value part in the pair, which is the second element.
- Class gov.sandia.cognition.util.DefaultNamedValue extends AbstractNamed implements Serializable
  - Serialized Fields
    - value
```
java.lang.Object value
```
      The value.
- Class gov.sandia.cognition.util.DefaultPair extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - first
```
java.lang.Object first
```
      The first object.
    - second
```
java.lang.Object second
```
      The second object.
- Class gov.sandia.cognition.util.DefaultTemporalValue extends AbstractTemporal implements Serializable
  - Serialized Fields
    - value
```
java.lang.Object value
```
      The value associated with the time.
- Class gov.sandia.cognition.util.DefaultTriple extends AbstractCloneableSerializable implements Serializable
  - Serialized Fields
    - first
```
java.lang.Object first
```
      The first object.
    - second
```
java.lang.Object second
```
      The second object.
    - third
```
java.lang.Object third
```
      The third type.
- Class gov.sandia.cognition.util.DefaultWeightedPair extends DefaultPair<FirstType,SecondType> implements Serializable
  - Serialized Fields
    - weight
```
double weight
```
      The weight for the pair.
- Class gov.sandia.cognition.util.DefaultWeightedValue extends AbstractWeighted implements Serializable
  - Serialized Fields
    - value
```
java.lang.Object value
```
      The value.
- Class gov.sandia.cognition.util.DefaultWeightedValue.WeightComparator extends AbstractCloneableSerializable implements Serializable
- Class gov.sandia.cognition.util.DoubleReuseRandom extends java.util.Random implements Serializable
  - Serialized Fields
    - randArray
```
double[] randArray
```
      an array of pre-generated random numbers
    - randArrayIndex
```
int randArrayIndex
```
      the current index randArray
    - initialized
```
boolean initialized
```
      whether or not the randArray has been filled with random numbers

Serialized Form

Package gov.sandia.cognition.algorithm

Class gov.sandia.cognition.algorithm.AbstractAnytimeAlgorithm extends AbstractIterativeAlgorithm implements Serializable

Serialized Fields

maxIterations

Class gov.sandia.cognition.algorithm.AbstractIterativeAlgorithm extends AbstractCloneableSerializable implements Serializable

Serialized Fields

iteration

Class gov.sandia.cognition.algorithm.AbstractParallelAlgorithm extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.algorithm.AnytimeAlgorithmWrapper extends AbstractIterativeAlgorithm implements Serializable

Serialization Methods

readResolve

Serialized Fields

algorithm

Package gov.sandia.cognition.algorithm.event

Class gov.sandia.cognition.algorithm.event.AbstractIterativeAlgorithmListener extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.algorithm.event.IterationMeasurablePerformanceReporter extends AbstractIterativeAlgorithmListener implements Serializable

Serialized Fields

out

format

Class gov.sandia.cognition.algorithm.event.IterationStartReporter extends AbstractIterativeAlgorithmListener implements Serializable

Serialized Fields

out

format

Package gov.sandia.cognition.collection

Class gov.sandia.cognition.collection.AbstractLogNumberMap extends AbstractScalarMap<KeyType,LogNumber> implements Serializable

Class gov.sandia.cognition.collection.AbstractMutableDoubleMap extends AbstractScalarMap<KeyType,MutableDouble> implements Serializable

Class gov.sandia.cognition.collection.AbstractScalarMap extends AbstractCloneableSerializable implements Serializable

Serialized Fields

map

Class gov.sandia.cognition.collection.DefaultComparator extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.collection.DefaultIndexer extends AbstractCloneableSerializable implements Serializable

Serialized Fields

valueList

valueToIndexMap

Class gov.sandia.cognition.collection.DefaultMultiCollection extends java.util.AbstractCollection<EntryType> implements Serializable

Serialized Fields

collections

Class gov.sandia.cognition.collection.DoubleArrayList extends gov.sandia.cognition.collection.PrimitiveArrayList implements Serializable

Serialized Fields

elements

Class gov.sandia.cognition.collection.DynamicArrayMap extends java.util.AbstractMap<java.lang.Integer,ValueType> implements Serializable

Serialized Fields

array

numValues

Class gov.sandia.cognition.collection.FiniteCapacityBuffer extends java.util.AbstractList<DataType> implements Serializable

Serialized Fields

data

head

size

Class gov.sandia.cognition.collection.IntArrayList extends gov.sandia.cognition.collection.PrimitiveArrayList implements Serializable

Serialized Fields

elements

Class gov.sandia.cognition.collection.IntegerSpan extends java.util.AbstractSet<java.lang.Integer> implements Serializable

Serialized Fields

minValue

maxValue

Class gov.sandia.cognition.collection.MultiIterator extends java.lang.Object implements Serializable

Serialized Fields

currentIterator

remainingIterators

Class gov.sandia.cognition.collection.NumberComparator extends AbstractCloneableSerializable implements Serializable

Package gov.sandia.cognition.data.convert

Class gov.sandia.cognition.data.convert.AbstractDataConverter extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.data.convert.AbstractReverseCachedDataConverter extends AbstractReversibleDataConverter<InputType,OutputType> implements Serializable

Class gov.sandia.cognition.data.convert.AbstractReversibleDataConverter extends AbstractDataConverter<InputType,OutputType> implements Serializable

Class gov.sandia.cognition.data.convert.IdentityDataConverter extends AbstractCloneableSerializable implements Serializable

Class gov.sandia.cognition.data.convert.ObjectToStringConverter extends AbstractDataConverter<java.lang.Object,java.lang.String> implements Serializable

Package gov.sandia.cognition.data.convert.number

Class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter extends AbstractReverseCachedDataConverter<java.lang.Boolean,java.lang.Number,DefaultBooleanToNumberConverter.Reverse> implements Serializable

Serialized Fields

trueValue

falseValue

nullValue

Class gov.sandia.cognition.data.convert.number.DefaultBooleanToNumberConverter.Reverse extends AbstractReversibleDataConverter<java.lang.Number,java.lang.Boolean> implements Serializable

Class gov.sandia.cognition.data.convert.number.StringToDoubleConverter extends AbstractReverseCachedDataConverter<java.lang.String,java.lang.Double,ObjectToStringConverter> implements Serializable

Class gov.sandia.cognition.data.convert.number.StringToIntegerConverter extends AbstractReverseCachedDataConverter<java.lang.String,java.lang.Integer,ObjectToStringConverter> implements Serializable

Package gov.sandia.cognition.data.convert.vector

Class gov.sandia.cognition.data.convert.vector.AbstractToVectorEncoder extends AbstractDataConverter<InputType,Vector> implements Serializable

Serialized Fields