- ObjectSerializationHandler - Class in gov.sandia.cognition.io
-
The ObjectSerializationHandler class implements methods for
handling the serialization and deserialization of objects.
- ObjectSerializationHandler() - Constructor for class gov.sandia.cognition.io.ObjectSerializationHandler
-
- objectToOptimize - Variable in class gov.sandia.cognition.learning.algorithm.regression.AbstractLogisticRegression
-
The object to optimize, used as a factory on successive runs of the
algorithm.
- ObjectToStringConverter - Class in gov.sandia.cognition.data.convert
-
Converts an Object to a String using the toString
method.
- ObjectToStringConverter() - Constructor for class gov.sandia.cognition.data.convert.ObjectToStringConverter
-
Creates a new ObjectToStringConverter.
- ObjectToStringTextualConverter - Class in gov.sandia.cognition.text.convert
-
A text converter that can take in any type of object and then returns a
new DefaultTextual that wraps that object's toString().
- ObjectToStringTextualConverter() - Constructor for class gov.sandia.cognition.text.convert.ObjectToStringTextualConverter
-
Creates a new ObjectToStringTextualConverter.
- ObjectUtil - Class in gov.sandia.cognition.util
-
The ObjectUtil class implements static utility methods for dealing with
Objects.
- ObjectUtil() - Constructor for class gov.sandia.cognition.util.ObjectUtil
-
- ObservationAssignmentTask(Collection<? extends ObservationType>) - Constructor for class gov.sandia.cognition.statistics.bayesian.ParallelDirichletProcessMixtureModel.ObservationAssignmentTask
-
Creates a new instance of ObservationAssignmentTask
- ObservationLikelihoodTask() - Constructor for class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ObservationLikelihoodTask
-
Default constructor.
- observationLikelihoodTasks - Variable in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel
-
Observation likelihood tasks
- observationModel - Variable in class gov.sandia.cognition.statistics.bayesian.ExtendedKalmanFilter
-
Model that determines how the state is observed.
- observations - Variable in class gov.sandia.cognition.learning.algorithm.hmm.ParallelHiddenMarkovModel.ObservationLikelihoodTask
-
Observations
- OccurrenceInText<DataType> - Interface in gov.sandia.cognition.text
-
An interface for a marker that some data occurred in some span of text.
- occurrenceTopicAssignments - Variable in class gov.sandia.cognition.text.topic.LatentDirichletAllocationVectorGibbsSampler
-
The assignments of term occurrences to topics.
- offer(PairType, double) - Method in class gov.sandia.cognition.math.geometry.KDTree.Neighborhood
-
Offers the neighbor if there is space or it's closer than the
furthest neighbor.
- offset - Variable in class gov.sandia.cognition.learning.function.scalar.LinearFunction
-
The offset (b).
- oneMinusDampingFactor - Variable in class gov.sandia.cognition.learning.algorithm.clustering.AffinityPropagation
-
The cached value of one minus the damping factor.
- OnlineBaggingCategorizerLearner<InputType,CategoryType,MemberType extends Evaluator<? super InputType,? extends CategoryType>> - Class in gov.sandia.cognition.learning.algorithm.ensemble
-
An implementation of an online version of the Bagging algorithm for learning
an ensemble of categorizers.
- OnlineBaggingCategorizerLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner
-
Creates a new OnlineBaggingCategorizerLearner with a null learner
and default parameters.
- OnlineBaggingCategorizerLearner(IncrementalLearner<? super InputOutputPair<? extends InputType, CategoryType>, MemberType>) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner
-
Creates a new OnlineBaggingCategorizerLearner with the given
base learner and default parameters.
- OnlineBaggingCategorizerLearner(IncrementalLearner<? super InputOutputPair<? extends InputType, CategoryType>, MemberType>, int, double, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.OnlineBaggingCategorizerLearner
-
Creates a new OnlineBaggingCategorizerLearner with the given
parameters.
- OnlineBinaryMarginInfusedRelaxedAlgorithm - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
An implementation of the binary MIRA algorithm.
- OnlineBinaryMarginInfusedRelaxedAlgorithm() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm
-
Creates a new OnlineBinaryMarginInfusedRelaxedAlgorithm with
default parameters.
- OnlineBinaryMarginInfusedRelaxedAlgorithm(double) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm
-
Creates a new OnlineBinaryMarginInfusedRelaxedAlgorithm with
the given minimum margin.
- OnlineBinaryMarginInfusedRelaxedAlgorithm(double, VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineBinaryMarginInfusedRelaxedAlgorithm
-
Creates a new OnlineBinaryMarginInfusedRelaxedAlgorithm with
the new minimum margin.
- OnlineKernelPerceptron<InputType> - Class in gov.sandia.cognition.learning.algorithm.perceptron.kernel
-
An implementation of the online version of the Perceptron algorithm.
- OnlineKernelPerceptron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.OnlineKernelPerceptron
-
Creates a new OnlineKernelPerceptron with no kernel.
- OnlineKernelPerceptron(Kernel<? super InputType>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.OnlineKernelPerceptron
-
Creates a new OnlineKernelPerceptron with the given kernel.
- OnlineKernelRandomizedBudgetPerceptron<InputType> - Class in gov.sandia.cognition.learning.algorithm.perceptron.kernel
-
An implementation of a fixed-memory kernel Perceptron algorithm.
- OnlineKernelRandomizedBudgetPerceptron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.OnlineKernelRandomizedBudgetPerceptron
-
Creates a new OnlineKernelRandomizedBudgetPerceptron with default
parameters and a null kernel.
- OnlineKernelRandomizedBudgetPerceptron(Kernel<? super InputType>, int, Random) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.kernel.OnlineKernelRandomizedBudgetPerceptron
-
Creates a new OnlineKernelRandomizedBudgetPerceptron with the
given parameters.
- OnlineLearner() - Constructor for class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.OnlineLearner
-
Creates a new learner with a null distribution learner.
- OnlineLearner(IncrementalLearner<? super Double, DistributionType>) - Constructor for class gov.sandia.cognition.learning.algorithm.bayes.VectorNaiveBayesCategorizer.OnlineLearner
-
Creates a new learner with a given distribution learner.
- OnlineLearnerValidationExperiment<DataType,LearnedType,StatisticType,SummaryType> - Class in gov.sandia.cognition.learning.experiment
-
Implements an experiment where an incremental supervised machine learning
algorithm is evaluated by applying it to a set of data by successively
testing on each item and then training on it.
- OnlineLearnerValidationExperiment() - Constructor for class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment
-
Creates a new instance of IncrementalLearnerValidationExperiment.
- OnlineLearnerValidationExperiment(PerformanceEvaluator<? super LearnedType, ? super Collection<? extends DataType>, ? extends StatisticType>, Summarizer<? super StatisticType, ? extends SummaryType>) - Constructor for class gov.sandia.cognition.learning.experiment.OnlineLearnerValidationExperiment
-
Creates a new instance of IncrementalLearnerValidationExperiment.
- OnlineMultiPerceptron<CategoryType> - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
An online, multiple category version of the Perceptron algorithm.
- OnlineMultiPerceptron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron
-
Creates a new OnlineMultiPerceptron.
- OnlineMultiPerceptron(double) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron
-
Creates a new OnlineMultiPerceptron with the
given minimum margin.
- OnlineMultiPerceptron(double, VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron
-
Creates a new OnlineMultiPerceptron with the
given minimum margin and backing vector factory.
- OnlineMultiPerceptron.ProportionalUpdate<CategoryType> - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
Variant of a multi-category Perceptron that performs a proportional
weight update on all categories that are scored higher than the true
category such that the weights sum to 1.0 and are proportional how much
larger the score was for each incorrect category than the true category.
- OnlineMultiPerceptron.UniformUpdate<CategoryType> - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
Variant of a multi-category Perceptron that performs a uniform weight
update on all categories that are scored higher than the true category
such that the weights are equal and sum to -1.
- OnlinePassiveAggressivePerceptron - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
An implementation of the Passive-Aggressive algorithm for learning a linear
binary categorizer.
- OnlinePassiveAggressivePerceptron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron
-
Creates a new OnlinePassiveAggressivePerceptron.
- OnlinePassiveAggressivePerceptron(VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePassiveAggressivePerceptron
-
Creates a new OnlinePassiveAggressivePerceptron with the given
vector factory.
- OnlinePassiveAggressivePerceptron.AbstractSoftMargin - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
An abstract class for soft-margin versions of the Passive-Aggressive
algorithm.
- OnlinePassiveAggressivePerceptron.LinearSoftMargin - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
An implementation of the linear soft-margin variant of the Passive-
Aggressive algorithm (PA-I).
- OnlinePassiveAggressivePerceptron.QuadraticSoftMargin - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
An implementation of the quadratic soft-margin variant of the Passive-
Aggressive algorithm (PA-II).
- OnlinePerceptron - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
An online version of the classic Perceptron algorithm.
- OnlinePerceptron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePerceptron
-
Creates a new OnlinePerceptron.
- OnlinePerceptron(VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlinePerceptron
-
Creates a new OnlinePerceptron with the given vector factory.
- OnlineRampPassiveAggressivePerceptron - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
An implementation of the Ramp Loss Passive Aggressive Perceptron (PA^R) from
the referenced paper.
- OnlineRampPassiveAggressivePerceptron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineRampPassiveAggressivePerceptron
-
Creates a new OnlineRampPassiveAggressivePerceptron with default parameters.
- OnlineRampPassiveAggressivePerceptron(double) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineRampPassiveAggressivePerceptron
-
Creates a new OnlineRampPassiveAggressivePerceptron with the given
aggressiveness.
- OnlineRampPassiveAggressivePerceptron(double, VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineRampPassiveAggressivePerceptron
-
Creates a new OnlineRampPassiveAggressivePerceptron with the given parameters.
- OnlineShiftingPerceptron - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
An implementation of the Shifting Perceptron algorithm.
- OnlineShiftingPerceptron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron
-
Creates a new OnlineShiftingPerceptron with default parameters.
- OnlineShiftingPerceptron(double) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron
-
Creates a new OnlineShiftingPerceptron with the given parameters.
- OnlineShiftingPerceptron(double, VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineShiftingPerceptron
-
Creates a new OnlineShiftingPerceptron with the given parameters.
- OnlineShiftingPerceptron.LinearResult - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
This is the result learned by the shifting perceptron.
- OnlineVotedPerceptron - Class in gov.sandia.cognition.learning.algorithm.perceptron
-
An online version of the Voted-Perceptron algorithm.
- OnlineVotedPerceptron() - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineVotedPerceptron
-
Creates a new OnlinePerceptron.
- OnlineVotedPerceptron(VectorFactory<?>) - Constructor for class gov.sandia.cognition.learning.algorithm.perceptron.OnlineVotedPerceptron
-
Creates a new OnlinePerceptron with the given vector factory.
- OperationNotConvergedException - Exception in gov.sandia.cognition.math
-
The OperationNotConvergedException class is an exception that
is thrown when some mathematical operation does not converge, when it is
expected to converge.
- OperationNotConvergedException(String) - Constructor for exception gov.sandia.cognition.math.OperationNotConvergedException
-
Creates a new OperationNotConvergedException.
- OperationNotConvergedException(String, Throwable) - Constructor for exception gov.sandia.cognition.math.OperationNotConvergedException
-
Creates a new OperationNotConvergedException.
- OperationNotConvergedException(Throwable) - Constructor for exception gov.sandia.cognition.math.OperationNotConvergedException
-
Creates a new OperationNotConvergedException.
- OPTIMAL_THREADS - Static variable in class gov.sandia.cognition.algorithm.ParallelUtil
-
Indicates to the createThreadPool() method to estimate the "optimal"
number of threads for the computer currently executing the codes.
- OptimizedKMeansClusterer<DataType> - Class in gov.sandia.cognition.learning.algorithm.clustering
-
This class implements an optimized version of the k-means algorithm that
makes use of the triangle inequality to compute the same answer as k-means
while using less distance calculations.
- OptimizedKMeansClusterer(int, int, FixedClusterInitializer<CentroidCluster<DataType>, DataType>, Metric<? super DataType>, ClusterCreator<CentroidCluster<DataType>, DataType>) - Constructor for class gov.sandia.cognition.learning.algorithm.clustering.OptimizedKMeansClusterer
-
Creates a new instance of OptimizedKMeansClusterer.
- optimizeEdges() - Method in class gov.sandia.cognition.graph.DenseMemoryGraph
-
This private helper sorts all edges for quicker edge-lookup times.
- out - Variable in class gov.sandia.cognition.algorithm.event.IterationMeasurablePerformanceReporter
-
The print stream to report performance to.
- out - Variable in class gov.sandia.cognition.algorithm.event.IterationStartReporter
-
The print stream to report performance to.
- out - Variable in class gov.sandia.cognition.learning.performance.AnytimeBatchLearnerValidationPerformanceReporter
-
The print stream to report performance to.
- out - Variable in class gov.sandia.cognition.text.topic.ProbabilisticLatentSemanticAnalysis.StatusPrinter
-
The stream to write the status to.
- outerProduct(Vector) - Method in class gov.sandia.cognition.math.matrix.AbstractVector
-
- outerProduct(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
-
- outerProduct(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.DenseVector
-
- outerProduct(DenseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
-
- outerProduct(SparseVector) - Method in class gov.sandia.cognition.math.matrix.custom.SparseVector
-
- outerProduct(Vector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
-
- outerProduct(AbstractMTJVector) - Method in class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector
-
Computes the outer matrix product between the two vectors
- outerProduct(AbstractMTJVector) - Method in class gov.sandia.cognition.math.matrix.mtj.DenseVector
-
- outerProduct(AbstractMTJVector) - Method in class gov.sandia.cognition.math.matrix.mtj.SparseVector
-
- outerProduct(Vector) - Method in interface gov.sandia.cognition.math.matrix.Vector
-
Computes the outer matrix product between the two vectors
- outlierPercent - Variable in class gov.sandia.cognition.learning.data.feature.StandardDistributionNormalizer.Learner
-
The percentage of outliers to exclude from learning.
- outOfBagCorrect - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria
-
A boolean for each example indicating whether or not it is
currently a correct or incorrect out-of-bag vote.
- outOfBagErrorCount - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.AbstractCategorizerOutOfBagStoppingCriteria
-
The total number of out-of-bag errors.
- OutOfBagErrorStoppingCriteria() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner.OutOfBagErrorStoppingCriteria
-
Creates a new OutOfBagErrorStoppingCriteria.
- OutOfBagErrorStoppingCriteria(int) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner.OutOfBagErrorStoppingCriteria
-
Creates a new OutOfBagErrorStoppingCriteria with the given
smoothing window size.
- OutOfBagErrorStoppingCriteria() - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner.OutOfBagErrorStoppingCriteria
-
Creates a new OutOfBagErrorStoppingCriteria.
- OutOfBagErrorStoppingCriteria(int) - Constructor for class gov.sandia.cognition.learning.algorithm.ensemble.IVotingCategorizerLearner.OutOfBagErrorStoppingCriteria
-
Creates a new OutOfBagErrorStoppingCriteria with the given
smoothing window size.
- outOfBagEstimates - Variable in class gov.sandia.cognition.learning.algorithm.ensemble.BaggingCategorizerLearner.OutOfBagErrorStoppingCriteria
-
The running estimate of the ensemble for each example where an ensemble
member can only vote on elements that were not in the bag used to train
it.
- output - Variable in class gov.sandia.cognition.framework.learning.EvaluatorBasedCognitiveModule
-
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
- output - Variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation.Entry
-
The output represented as a raw boolean, to enforce that the label
exists.
- outputCategory - Variable in class gov.sandia.cognition.learning.algorithm.tree.CategorizationTreeNode
-
The output category of the node.
- outputDimensionality - Variable in class gov.sandia.cognition.learning.data.feature.FeatureHashing
-
The output size of the hash.
- outputDouble - Variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation.Entry
-
The output converted to a double form (+1.0 or -1.0).
- outputLearner - Variable in class gov.sandia.cognition.learning.algorithm.InputOutputTransformedBatchLearner
-
The unsupervised learning algorithm for creating the output
transformation, which must be reversible for evaluation.
- outputsList(Iterable<? extends InputOutputPair<?, ? extends OutputType>>) - Static method in class gov.sandia.cognition.learning.data.DatasetUtil
-
Creates a list containing all of the output values from the given data.
- outputVariance - Variable in class gov.sandia.cognition.statistics.bayesian.BayesianLinearRegression
-
Assumed known variance of the outputs (measurements),
must be greater than zero.
- OverconstrainedConjugateGradientMatrixMinimizer - Class in gov.sandia.cognition.learning.algorithm.minimization.matrix
-
Implements a overconstrained conjugate gradient matrix optimizer.
- OverconstrainedConjugateGradientMatrixMinimizer(Vector, Vector) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.OverconstrainedConjugateGradientMatrixMinimizer
-
Initializes a steepest-descent solver with the minimum values
- OverconstrainedConjugateGradientMatrixMinimizer(Vector, Vector, double) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.OverconstrainedConjugateGradientMatrixMinimizer
-
Initializes a steepest-descent solver with some additional parameters
- OverconstrainedConjugateGradientMatrixMinimizer(Vector, Vector, double, int) - Constructor for class gov.sandia.cognition.learning.algorithm.minimization.matrix.OverconstrainedConjugateGradientMatrixMinimizer
-
Initializes a steepest-descent solver with all user-definable parameters
- OverconstrainedMatrixVectorMultiplier - Class in gov.sandia.cognition.learning.algorithm.minimization.matrix
-
Implements an overconstrainted matrix-vector multiplication.
- overrelaxation - Variable in class gov.sandia.cognition.learning.algorithm.svm.SuccessiveOverrelaxation
-
The overrelaxation parameter.