Uses of Interface
gov.sandia.cognition.util.Pair

Packages that use Pair

Package	Description
gov.sandia.cognition.evaluator	Provides interfaces and classes to do with the Evaluator interface.
gov.sandia.cognition.framework.learning.converter	Provides implementations of CogxelConverters.
gov.sandia.cognition.graph
gov.sandia.cognition.graph.inference
gov.sandia.cognition.learning.algorithm	Provides general interfaces for learning algorithms.
gov.sandia.cognition.learning.algorithm.genetic	Provides a genetic algorithm implementation.
gov.sandia.cognition.learning.algorithm.hmm	Provides hidden Markov model (HMM) algorithms.
gov.sandia.cognition.learning.algorithm.minimization.line	Provides line (scalar) minimization algorithms.
gov.sandia.cognition.learning.algorithm.regression	Provides regression algorithms, such as Linear Regression.
gov.sandia.cognition.learning.data	Provides data set utilities for learning.
gov.sandia.cognition.learning.experiment	Provides experiments for validating the performance of learning algorithms.
gov.sandia.cognition.learning.function.categorization	Provides functions that output a discrete set of categories.
gov.sandia.cognition.learning.function.cost	Provides cost functions.
gov.sandia.cognition.learning.performance.categorization	Provides performance measures for categorizers.
gov.sandia.cognition.math	Provides classes for mathematical computation.
gov.sandia.cognition.math.geometry	Provides classes and interfaces for computational geometry.
gov.sandia.cognition.math.matrix	Provides interfaces and classes for linear algebra.
gov.sandia.cognition.math.matrix.mtj	Provides a linear algebra package implementation wrapper using the Matrix Toolkits for Java (MTJ) library.
gov.sandia.cognition.statistics	Provides the inheritance hierarchy for general statistical methods and distributions.
gov.sandia.cognition.statistics.bayesian	Provides algorithms for computing Bayesian estimates of parameters.
gov.sandia.cognition.statistics.method	Provides algorithms for evaluating statistical data and conducting statistical inference, particularly frequentist methods.
gov.sandia.cognition.text.evaluation	Provides methods for evaluating text processing algorithms.
gov.sandia.cognition.util	Provides general utility classes.

Uses of Pair in gov.sandia.cognition.evaluator

Classes in gov.sandia.cognition.evaluator that implement Pair

Modifier and Type	Class and Description
class	CompositeEvaluatorPair<InputType,IntermediateType,OutputType> Implements a composition of two evaluators.

Uses of Pair in gov.sandia.cognition.framework.learning.converter

Classes in gov.sandia.cognition.framework.learning.converter with type parameters of type Pair

Modifier and Type	Class and Description
class	AbstractCogxelPairConverter<FirstType,SecondType,PairType extends Pair<FirstType,SecondType>> Partial implementation of CogxelConverters based on a Pair

Uses of Pair in gov.sandia.cognition.graph

Methods in gov.sandia.cognition.graph that return Pair

Modifier and Type	Method and Description
Pair<java.lang.Integer,java.lang.Integer>	DenseMemoryGraph.getEdgeEndpointIds(int i) Helper that returns the endpoint values for the input edge id.
Pair<java.lang.Integer,java.lang.Integer>	DirectedNodeEdgeGraph.getEdgeEndpointIds(int id) Return the edge endpoints (by node id) for edge id (where id [0 ...

Methods in gov.sandia.cognition.graph that return types with arguments of type Pair

Modifier and Type	Method and Description
java.util.Set<Pair<java.lang.Integer,java.lang.Integer>>	GraphMetrics.getNodeTriangleEndpointIds(int nodeId) Returns the other two endpoint ids for all triangles the node participates in.
java.util.Set<Pair<java.lang.Integer,java.lang.Integer>>	GraphMetrics.getNodeTriangleEndpointIds(NodeNameType nodeName) Returns the other two endpoint ids for all triangles the node participates in.
java.util.Set<Pair<NodeNameType,NodeNameType>>	GraphMetrics.getNodeTriangleEndpoints(int nodeId) Returns the other two endpoint names for all triangles the node participates in.
java.util.Set<Pair<NodeNameType,NodeNameType>>	GraphMetrics.getNodeTriangleEndpoints(NodeNameType nodeName) Returns the other two endpoint names for all triangles the node participates in.
java.util.Collection<Pair<NodeNameType,java.lang.Double>>	DirectedWeightedNodeEdgeGraph.getSuccessorsWithWeights(NodeNameType node) Returns all the nodes this node connects to with edge weights (outgoing edges only).
java.util.Collection<Pair<NodeNameType,java.lang.Double>>	WeightedDenseMemoryGraph.getSuccessorsWithWeights(NodeNameType node) Execution: O(log m + d) where d is the degree of the specified node (which can be O(m) but is usually O(1)).

Uses of Pair in gov.sandia.cognition.graph.inference

Methods in gov.sandia.cognition.graph.inference that return Pair

Modifier and Type	Method and Description
Pair<java.lang.Integer,java.lang.Integer>	CostSpeedupEnergyFunction.getEdge(int i)
Pair<java.lang.Integer,java.lang.Integer>	EdgeMergingEnergyFunction.getEdge(int i)
Pair<java.lang.Integer,java.lang.Integer>	EnergyFunction.getEdge(int i) Returns the indices for the two endpoints in the specified path.
Pair<java.lang.Integer,java.lang.Integer>	GraphWrappingEnergyFunction.getEdge(int i)

Uses of Pair in gov.sandia.cognition.learning.algorithm

Classes in gov.sandia.cognition.learning.algorithm that implement Pair

Modifier and Type	Class and Description
class	CompositeBatchLearnerPair<InputType,IntermediateType,OutputType> Composes together a pair of batch (typically unsupervised) learners.

Uses of Pair in gov.sandia.cognition.learning.algorithm.genetic

Classes in gov.sandia.cognition.learning.algorithm.genetic that implement Pair

Modifier and Type	Class and Description
class	EvaluatedGenome<GenomeType> The EvaluatedGenome class wraps together a Genome and its cost score.

Uses of Pair in gov.sandia.cognition.learning.algorithm.hmm

Methods in gov.sandia.cognition.learning.algorithm.hmm that return Pair

Modifier and Type	Method and Description
protected Pair<java.util.ArrayList<java.util.ArrayList<Vector>>,java.util.ArrayList<Matrix>>	BaumWelchAlgorithm.computeSequenceParameters() Computes the gammas and A matrices for each sequence.
protected Pair<Vector,int[]>	HiddenMarkovModel.computeViterbiRecursion(Vector delta, Vector bn) Computes the Viterbi recursion for a given "delta" and "b"
protected Pair<Vector,int[]>	ParallelHiddenMarkovModel.computeViterbiRecursion(Vector delta, Vector bn)

Uses of Pair in gov.sandia.cognition.learning.algorithm.minimization.line

Classes in gov.sandia.cognition.learning.algorithm.minimization.line that implement Pair

Modifier and Type	Class and Description
class	InputOutputSlopeTriplet Stores an InputOutputPair with corresponding slope (gradient) information

Uses of Pair in gov.sandia.cognition.learning.algorithm.regression

Classes in gov.sandia.cognition.learning.algorithm.regression that implement Pair

Modifier and Type	Class and Description
static class	LogisticRegression.Function Class that is a linear discriminant, followed by a sigmoid function.

Uses of Pair in gov.sandia.cognition.learning.data

Subinterfaces of Pair in gov.sandia.cognition.learning.data

Modifier and Type	Interface and Description
interface	InputOutputPair<InputType,OutputType> The InputOutputPair interface is just a container for an input and its associated output used in supervised learning.
interface	TargetEstimatePair<TargetType,EstimateType> A Pair that encapsulates a target-estimate Pair.
interface	ValueDiscriminantPair<ValueType,DiscriminantType extends java.lang.Comparable<? super DiscriminantType>> Interface for a pair of a value and a discriminant for ordering instances that have the same value.
interface	WeightedInputOutputPair<InputType,OutputType> The WeightedInputOutputPair class implements an additional weighting term on an InputOutputPair, typically used to inform learning algorithms of the relative weight between examples.
interface	WeightedTargetEstimatePair<TargetType,EstimateType> Extends TargetEstimatePair with an additional weight field.

Classes in gov.sandia.cognition.learning.data that implement Pair

Modifier and Type	Class and Description
class	AbstractInputOutputPair<InputType,OutputType> An abstract implementation of the InputOutputPair interface.
class	AbstractTargetEstimatePair<TargetType,EstimateType> An abstract implementation of the TargetEstimatePair.
class	AbstractValueDiscriminantPair<ValueType,DiscriminantType extends java.lang.Comparable<? super DiscriminantType>> An abstract implementation of the ValueDiscriminantPair interface.
class	DefaultInputOutputPair<InputType,OutputType> A default implementation of the InputOutputPair interface.
class	DefaultTargetEstimatePair<TargetType,EstimateType> A default implementation of the TargetEstimatePair.
class	DefaultValueDiscriminantPair<ValueType,DiscriminantType extends java.lang.Comparable<? super DiscriminantType>> A default implementation of the ValueDiscriminantPair interface.
class	DefaultWeightedInputOutputPair<InputType,OutputType> A default implementation of the WeightedInputOutputPair interface.
class	DefaultWeightedTargetEstimatePair<TargetType,EstimateType> Extends TargetEstimatePair with an additional weight field.
class	DefaultWeightedValueDiscriminant<ValueType> An implementation of ValueDiscriminantPair that stores a double as the discriminant.

Constructors in gov.sandia.cognition.learning.data with parameters of type Pair

Constructor and Description
DefaultInputOutputPair(Pair<? extends InputType,? extends OutputType> pair) Creates a new DefaultInputOutputPair using the first element of the given pair as the input and the second element of the given pair as the output.
DefaultTargetEstimatePair(Pair<? extends TargetType,? extends EstimateType> other) Creates a shallow copy of another target-estimate pair.
DefaultWeightedInputOutputPair(Pair<? extends InputType,? extends OutputType> pair, double weight) Creates a new DefaultWeightedInputOutputPair with the given input and output from the given pair plus a weight.

Uses of Pair in gov.sandia.cognition.learning.experiment

Fields in gov.sandia.cognition.learning.experiment declared as Pair

Modifier and Type	Field and Description
protected Pair<BatchLearner<? super java.util.Collection<? extends FoldDataType>,? extends LearnedType>,BatchLearner<? super java.util.Collection<? extends FoldDataType>,? extends LearnedType>>	LearnerComparisonExperiment.learners The learners that the experiment is being performed on.

Methods in gov.sandia.cognition.learning.experiment that return Pair

Modifier and Type	Method and Description
Pair<BatchLearner<? super java.util.Collection<? extends FoldDataType>,? extends LearnedType>,BatchLearner<? super java.util.Collection<? extends FoldDataType>,? extends LearnedType>>	LearnerComparisonExperiment.getLearners() Gets the learners the experiment is being run on.

Methods in gov.sandia.cognition.learning.experiment with parameters of type Pair

Modifier and Type	Method and Description
LearnerComparisonExperiment.Result<SummaryType>	LearnerComparisonExperiment.evaluate(Pair<BatchLearner<? super java.util.Collection<? extends FoldDataType>,? extends LearnedType>,BatchLearner<? super java.util.Collection<? extends FoldDataType>,? extends LearnedType>> learners, java.util.Collection<? extends InputDataType> data) Evaluates the two batch learners using the given data on the same set of validation folds and returns the resulting information including the confidence statistic that the two are different along with the summary of their performance.
protected void	LearnerComparisonExperiment.setLearners(Pair<BatchLearner<? super java.util.Collection<? extends FoldDataType>,? extends LearnedType>,BatchLearner<? super java.util.Collection<? extends FoldDataType>,? extends LearnedType>> learners) Sets the learners the experiment is being run on.

Uses of Pair in gov.sandia.cognition.learning.function.categorization

Fields in gov.sandia.cognition.learning.function.categorization with type parameters of type Pair

Modifier and Type	Field and Description
protected java.util.Map<Pair<CategoryType,CategoryType>,Evaluator<? super InputType,java.lang.Boolean>>	BinaryVersusCategorizer.categoryPairsToEvaluatorMap Maps false-true category pairs .

Methods in gov.sandia.cognition.learning.function.categorization that return types with arguments of type Pair

Modifier and Type	Method and Description
java.util.Map<Pair<CategoryType,CategoryType>,Evaluator<? super InputType,java.lang.Boolean>>	BinaryVersusCategorizer.getCategoryPairsToEvaluatorMap() Gets the mapping of false-true category pairs to the binary categorizer that distinguishes them.

Method parameters in gov.sandia.cognition.learning.function.categorization with type arguments of type Pair

Modifier and Type	Method and Description
void	BinaryVersusCategorizer.setCategoryPairsToEvaluatorMap(java.util.Map<Pair<CategoryType,CategoryType>,Evaluator<? super InputType,java.lang.Boolean>> categoryPairsToEvaluatorMap) Sets the mapping of false-true category pairs to the binary categorizer that distinguishes them.

Constructor parameters in gov.sandia.cognition.learning.function.categorization with type arguments of type Pair

Constructor and Description
BinaryVersusCategorizer(java.util.Set<CategoryType> categories, java.util.Map<Pair<CategoryType,CategoryType>,Evaluator<? super InputType,java.lang.Boolean>> categoryPairsToEvaluatorMap) Creates a new BinaryVersusCategorizer.

Uses of Pair in gov.sandia.cognition.learning.function.cost

Classes in gov.sandia.cognition.learning.function.cost that implement Pair

Modifier and Type	Class and Description
static class	SumSquaredErrorCostFunction.GradientPartialSSE Partial result from the SSE gradient computation

Uses of Pair in gov.sandia.cognition.learning.performance.categorization

Method parameters in gov.sandia.cognition.learning.performance.categorization with type arguments of type Pair

Modifier and Type	Method and Description
static DefaultBinaryConfusionMatrix	DefaultBinaryConfusionMatrix.createFromActualPredictedPairs(java.util.Collection<? extends Pair<? extends java.lang.Boolean,? extends java.lang.Boolean>> pairs) Creates a new DefaultConfusionMatrix from the given actual-predicted pairs.
static <CategoryType> DefaultConfusionMatrix<CategoryType>	DefaultConfusionMatrix.createFromActualPredictedPairs(java.util.Collection<? extends Pair<? extends CategoryType,? extends CategoryType>> pairs) Creates a new DefaultConfusionMatrix from the given actual-predicted pairs.
DefaultBinaryConfusionMatrix	DefaultBinaryConfusionMatrix.ActualPredictedPairSummarizer.summarize(java.util.Collection<? extends Pair<? extends java.lang.Boolean,? extends java.lang.Boolean>> data)
DefaultConfusionMatrix<CategoryType>	DefaultConfusionMatrix.ActualPredictedPairSummarizer.summarize(java.util.Collection<? extends Pair<? extends CategoryType,? extends CategoryType>> data)

Uses of Pair in gov.sandia.cognition.math

Methods in gov.sandia.cognition.math that return Pair

Modifier and Type	Method and Description
static Pair<Vector,Matrix>	MultivariateStatisticsUtil.computeMeanAndCovariance(java.lang.Iterable<? extends Vectorizable> data) Computes the mean and unbiased covariance Matrix of a multivariate data set.
static Pair<java.lang.Double,java.lang.Double>	UnivariateStatisticsUtil.computeMeanAndVariance(java.lang.Iterable<? extends java.lang.Number> data) Computes the mean and unbiased variance of a Collection of data using the one-pass approach.
static Pair<java.lang.Double,java.lang.Double>	UnivariateStatisticsUtil.computeMinAndMax(java.lang.Iterable<? extends java.lang.Number> data) Computes the minimum and maximum of a set of data in a single pass.
static Pair<Vector,Matrix>	MultivariateStatisticsUtil.computeWeightedMeanAndCovariance(java.lang.Iterable<? extends WeightedValue<? extends Vectorizable>> data) Computes the mean and biased covariance Matrix of a multivariate weighted data set.
static Pair<java.lang.Double,java.lang.Double>	UnivariateStatisticsUtil.computeWeightedMeanAndVariance(java.lang.Iterable<? extends WeightedValue<? extends java.lang.Number>> data) Computes the mean and unbiased variance of a Collection of data using the one-pass approach.

Uses of Pair in gov.sandia.cognition.math.geometry

Classes in gov.sandia.cognition.math.geometry with type parameters of type Pair

Modifier and Type	Class and Description
class	KDTree<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> Implementation of a kd-tree.
protected static class	KDTree.InOrderKDTreeIterator<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> Iterates through the KDTree using "inorder", also known as "symmetric traversal", of the tree.
protected static class	KDTree.Neighborhood<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> A Collection of nearby pairs.
protected class	KDTree.Neighborhood.Neighbor<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> Holds neighbor information used during the evaluate method and is put into a priority queue.

Fields in gov.sandia.cognition.math.geometry declared as Pair

Modifier and Type	Field and Description
PairType	KDTree.InOrderKDTreeIterator.nodeValue Value of the node
protected PairType	KDTree.value VectorType,DataType value for this node of the subtree.

Methods in gov.sandia.cognition.math.geometry with type parameters of type Pair

Modifier and Type	Method and Description
static <VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>> KDTree<VectorType,DataType,PairType>	KDTree.createBalanced(java.util.Collection<? extends PairType> points) Creates a balanced KDTree based on the given collection of Pairs.

Methods in gov.sandia.cognition.math.geometry with parameters of type Pair

Modifier and Type	Method and Description
int	KDTree.PairFirstVectorizableIndexComparator.compare(Pair<? extends Vectorizable,?> o1, Pair<? extends Vectorizable,?> o2)
int	KDTree.PairFirstVectorizableIndexComparator.compare(Pair<? extends Vectorizable,?> o1, Pair<? extends Vectorizable,?> o2)

Uses of Pair in gov.sandia.cognition.math.matrix

Subinterfaces of Pair in gov.sandia.cognition.math.matrix

Modifier and Type	Interface and Description
interface	Vector2D An interface for a 2-dimensional vector.

Uses of Pair in gov.sandia.cognition.math.matrix.mtj

Classes in gov.sandia.cognition.math.matrix.mtj that implement Pair

Modifier and Type	Class and Description
class	Vector2 Implements a two-dimensional MTJ DenseVector.

Uses of Pair in gov.sandia.cognition.statistics

Methods in gov.sandia.cognition.statistics that return Pair

Modifier and Type	Method and Description
Pair<java.lang.Double,java.util.HashMap<TransferEntropy.TransferEntropyDistributionObject,TransferEntropy.TransferEntropyPartialSumObject>>	TransferEntropy.computeWithPartialSums() Computes the transfer entropy value and returns a map of the states with their corresponding partial sums.

Uses of Pair in gov.sandia.cognition.statistics.bayesian

Classes in gov.sandia.cognition.statistics.bayesian that implement Pair

Modifier and Type	Class and Description
static class	AdaptiveRejectionSampling.Point An InputOutputPair that has a natural ordering according to their input (x-axis) values.

Uses of Pair in gov.sandia.cognition.statistics.method

Methods in gov.sandia.cognition.statistics.method that return Pair

Modifier and Type	Method and Description
Pair<java.lang.Double,ClosedFormComputableDistribution<DataType>>	MaximumLikelihoodDistributionEstimator.DistributionEstimationTask.call()

Method parameters in gov.sandia.cognition.statistics.method with type arguments of type Pair

Modifier and Type	Method and Description
static ReceiverOperatingCharacteristic	ReceiverOperatingCharacteristic.createFromTargetEstimatePairs(java.util.Collection<? extends Pair<java.lang.Boolean,? extends java.lang.Number>> data) Creates an ROC curve based on the scored data with target information.

Uses of Pair in gov.sandia.cognition.text.evaluation

Subinterfaces of Pair in gov.sandia.cognition.text.evaluation

Modifier and Type	Interface and Description
interface	PrecisionRecallPair A pair of precision and recall values.

Classes in gov.sandia.cognition.text.evaluation that implement Pair

Modifier and Type	Class and Description
class	DefaultPrecisionRecallPair A default implementation of the PrecisionRecallPair interface.

Uses of Pair in gov.sandia.cognition.util

Subinterfaces of Pair in gov.sandia.cognition.util

Modifier and Type	Interface and Description
interface	KeyValuePair<KeyType,ValueType> Represents a key-value pair.
interface	WeightedPair<FirstType,SecondType> The WeightedPair interface defines an extension of a normal Pair that includes an additional weight.

Classes in gov.sandia.cognition.util that implement Pair

Modifier and Type	Class and Description
class	DefaultKeyValuePair<KeyType,ValueType> A default implementation of the KeyValuePair interface.
class	DefaultPair<FirstType,SecondType> The DefaultPair class implements a simple structure for a pair of two objects, potentially of different types.
class	DefaultTemporalValue<ValueType> The DefaultTemporalValue class is a default implementation of the TemporalValue interface.
class	DefaultWeightedPair<FirstType,SecondType> The DefaultWeightedPair class extends the DefaultPair class to add a weight to the pair.

Methods in gov.sandia.cognition.util with parameters of type Pair

Modifier and Type	Method and Description
boolean	DefaultPair.equals(Pair<FirstType,SecondType> other)

Constructors in gov.sandia.cognition.util with parameters of type Pair

Constructor and Description
DefaultPair(Pair<? extends FirstType,? extends SecondType> other) Copy constructor.