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

Packages that use Pair
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.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.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
 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
 class AbstractCogxelPairConverter<FirstType,SecondType,PairType extends Pair<FirstType,SecondType>>
          Partial implementation of CogxelConverters based on a Pair
 

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

Classes in gov.sandia.cognition.learning.algorithm that implement Pair
 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
 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
protected  Pair<ArrayList<ArrayList<Vector>>,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
 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
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
 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 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
 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 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 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
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
protected  Pair<BatchLearner<? super Collection<? extends FoldDataType>,? extends LearnedType>,BatchLearner<? super 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
 Pair<BatchLearner<? super Collection<? extends FoldDataType>,? extends LearnedType>,BatchLearner<? super 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
 LearnerComparisonExperiment.Result<SummaryType> LearnerComparisonExperiment.evaluate(Pair<BatchLearner<? super Collection<? extends FoldDataType>,? extends LearnedType>,BatchLearner<? super Collection<? extends FoldDataType>,? extends LearnedType>> learners, 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 Collection<? extends FoldDataType>,? extends LearnedType>,BatchLearner<? super 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
protected  Map<Pair<CategoryType,CategoryType>,Evaluator<? super InputType,Boolean>> BinaryVersusCategorizer.categoryPairsToEvaluatorMap
          Maps false-true category pairs .
 

Methods in gov.sandia.cognition.learning.function.categorization that return types with arguments of type Pair
 Map<Pair<CategoryType,CategoryType>,Evaluator<? super InputType,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
 void BinaryVersusCategorizer.setCategoryPairsToEvaluatorMap(Map<Pair<CategoryType,CategoryType>,Evaluator<? super InputType,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
BinaryVersusCategorizer(Set<CategoryType> categories, Map<Pair<CategoryType,CategoryType>,Evaluator<? super InputType,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
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
static DefaultBinaryConfusionMatrix DefaultBinaryConfusionMatrix.createFromActualPredictedPairs(Collection<? extends Pair<? extends Boolean,? extends Boolean>> pairs)
          Creates a new DefaultConfusionMatrix from the given actual-predicted pairs.
static
<CategoryType>
DefaultConfusionMatrix<CategoryType>
DefaultConfusionMatrix.createFromActualPredictedPairs(Collection<? extends Pair<? extends CategoryType,? extends CategoryType>> pairs)
          Creates a new DefaultConfusionMatrix from the given actual-predicted pairs.
 DefaultBinaryConfusionMatrix DefaultBinaryConfusionMatrix.ActualPredictedPairSummarizer.summarize(Collection<? extends Pair<? extends Boolean,? extends Boolean>> data)
           
 DefaultConfusionMatrix<CategoryType> DefaultConfusionMatrix.ActualPredictedPairSummarizer.summarize(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
static Pair<Vector,Matrix> MultivariateStatisticsUtil.computeMeanAndCovariance(Iterable<? extends Vectorizable> data)
          Computes the mean and unbiased covariance Matrix of a multivariate data set.
static Pair<Double,Double> UnivariateStatisticsUtil.computeMeanAndVariance(Iterable<? extends Number> data)
          Computes the mean and unbiased variance of a Collection of data using the one-pass approach.
static Pair<Double,Double> UnivariateStatisticsUtil.computeMinAndMax(Iterable<? extends Number> data)
          Computes the minimum and maximum of a set of data in a single pass.
static Pair<Vector,Matrix> MultivariateStatisticsUtil.computeWeightedMeanAndCovariance(Iterable<? extends WeightedValue<? extends Vectorizable>> data)
          Computes the mean and biased covariance Matrix of a multivariate weighted data set.
static Pair<Double,Double> UnivariateStatisticsUtil.computeWeightedMeanAndVariance(Iterable<? extends WeightedValue<? extends 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
 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
 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
static
<VectorType extends Vectorizable,DataType,PairType extends Pair<? extends VectorType,DataType>>
KDTree<VectorType,DataType,PairType>
KDTree.createBalanced(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
 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
 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
 class Vector2
          Implements a two-dimensional MTJ DenseVector.
 

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

Classes in gov.sandia.cognition.statistics.bayesian that implement Pair
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
 Pair<Double,ClosedFormComputableDistribution<DataType>> MaximumLikelihoodDistributionEstimator.DistributionEstimationTask.call()
           
 

Method parameters in gov.sandia.cognition.statistics.method with type arguments of type Pair
static ReceiverOperatingCharacteristic ReceiverOperatingCharacteristic.createFromTargetEstimatePairs(Collection<? extends Pair<Boolean,? extends 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
 interface PrecisionRecallPair
          A pair of precision and recall values.
 

Classes in gov.sandia.cognition.text.evaluation that implement Pair
 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
 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
 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
 boolean DefaultPair.equals(Pair<FirstType,SecondType> other)
           
 

Constructors in gov.sandia.cognition.util with parameters of type Pair
DefaultPair(Pair<? extends FirstType,? extends SecondType> other)
          Copy constructor.