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

Packages that use Summarizer

Package	Description
gov.sandia.cognition.learning.algorithm.nearest	Provides algorithms for Nearest-Neighbor memory-based functions.
gov.sandia.cognition.learning.experiment	Provides experiments for validating the performance of learning algorithms.
gov.sandia.cognition.learning.function.cost	Provides cost functions.
gov.sandia.cognition.learning.function.summarizer	Provides classes for summarizing data.
gov.sandia.cognition.learning.performance	Provides performance measures.
gov.sandia.cognition.learning.performance.categorization	Provides performance measures for categorizers.
gov.sandia.cognition.math	Provides classes for mathematical computation.
gov.sandia.cognition.statistics.method	Provides algorithms for evaluating statistical data and conducting statistical inference, particularly frequentist methods.

Uses of Summarizer in gov.sandia.cognition.learning.algorithm.nearest

Methods in gov.sandia.cognition.learning.algorithm.nearest that return Summarizer

Modifier and Type	Method and Description
Summarizer<? super OutputType,? extends OutputType>	AbstractKNearestNeighbor.getAverager() Getter for averager
Summarizer<? super OutputType,? extends OutputType>	KNearestNeighbor.getAverager() Getter for averager.

Methods in gov.sandia.cognition.learning.algorithm.nearest with parameters of type Summarizer

Modifier and Type	Method and Description
void	AbstractKNearestNeighbor.setAverager(Summarizer<? super OutputType,? extends OutputType> averager) Setter for averager
void	KNearestNeighbor.setAverager(Summarizer<? super OutputType,? extends OutputType> averager) Setter for averager.

Constructors in gov.sandia.cognition.learning.algorithm.nearest with parameters of type Summarizer

Constructor and Description
AbstractKNearestNeighbor(int k, DivergenceFunction<? super InputType,? super InputType> divergenceFunction, Summarizer<? super OutputType,? extends OutputType> averager) Creates a new instance of KNearestNeighbor
KNearestNeighborExhaustive(int k, java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>> data, DivergenceFunction<? super InputType,? super InputType> divergenceFunction, Summarizer<? super OutputType,? extends OutputType> averager) Creates a new instance of KNearestNeighborExhaustive
KNearestNeighborKDTree(int k, KDTree<InputType,OutputType,InputOutputPair<? extends InputType,OutputType>> data, Metric<? super InputType> distanceFunction, Summarizer<? super OutputType,? extends OutputType> averager) Creates a new instance of KNearestNeighborKDTree
Learner(int k, DivergenceFunction<? super InputType,? super InputType> divergenceFunction, Summarizer<? super OutputType,OutputType> averager) Creates a new instance of Learner
Learner(int k, Metric<? super Vectorizable> divergenceFunction, Summarizer<? super OutputType,? extends OutputType> averager) Creates a new instance of Learner
Learner(Summarizer<? super OutputType,? extends OutputType> averager) Creates a new instance of Learner.

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

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

Modifier and Type	Field and Description
protected Summarizer<? super StatisticType,? extends SummaryType>	LearnerComparisonExperiment.summarizer The summarizer for summarizing the result of the performance evaluator from all the folds.
protected Summarizer<? super StatisticType,? extends SummaryType>	LearnerRepeatExperiment.summarizer The summarizer for summarizing the result of the performance evaluator from all the folds.
protected Summarizer<? super StatisticType,? extends SummaryType>	LearnerValidationExperiment.summarizer The summarizer for summarizing the result of the performance evaluator from all the folds.
protected Summarizer<? super StatisticType,? extends SummaryType>	OnlineLearnerValidationExperiment.summarizer The summarizer for summarizing the result of the performance evaluator from all the folds.

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

Modifier and Type	Method and Description
Summarizer<? super StatisticType,? extends SummaryType>	LearnerComparisonExperiment.getSummarizer() Gets the summarizer of the performance evaluations.
Summarizer<? super StatisticType,? extends SummaryType>	LearnerRepeatExperiment.getSummarizer() Gets the summarizer of the performance evaluations.
Summarizer<? super StatisticType,? extends SummaryType>	LearnerValidationExperiment.getSummarizer() Gets the summarizer of the performance evaluations.
Summarizer<? super StatisticType,? extends SummaryType>	OnlineLearnerValidationExperiment.getSummarizer() Gets the summarizer of the performance evaluations.

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

Modifier and Type	Method and Description
void	LearnerComparisonExperiment.setSummarizer(Summarizer<? super StatisticType,? extends SummaryType> summarizer) Sets the summarizer of the performance evaluations.
void	LearnerRepeatExperiment.setSummarizer(Summarizer<? super StatisticType,? extends SummaryType> summarizer) Sets the summarizer of the performance evaluations.
void	LearnerValidationExperiment.setSummarizer(Summarizer<? super StatisticType,? extends SummaryType> summarizer) Sets the summarizer of the performance evaluations.
void	OnlineLearnerValidationExperiment.setSummarizer(Summarizer<? super StatisticType,? extends SummaryType> summarizer) Sets the summarizer of the performance evaluations.

Constructors in gov.sandia.cognition.learning.experiment with parameters of type Summarizer

Constructor and Description
LearnerComparisonExperiment(ValidationFoldCreator<InputDataType,FoldDataType> foldCreator, PerformanceEvaluator<? super LearnedType,? super java.util.Collection<? extends FoldDataType>,? extends StatisticType> performanceEvaluator, NullHypothesisEvaluator<java.util.Collection<? extends StatisticType>> statisticalTest, Summarizer<? super StatisticType,? extends SummaryType> summarizer) Creates a new instance of LearnerComparisonExperiment.
LearnerRepeatExperiment(int numTrials, PerformanceEvaluator<? super LearnedType,? super java.util.Collection<? extends InputDataType>,? extends StatisticType> performanceEvaluator, Summarizer<? super StatisticType,? extends SummaryType> summarizer) Creates a new instance of LearnerRepeatExperiment.
LearnerValidationExperiment(ValidationFoldCreator<InputDataType,FoldDataType> foldCreator, PerformanceEvaluator<? super LearnedType,? super java.util.Collection<? extends FoldDataType>,? extends StatisticType> performanceEvaluator, Summarizer<? super StatisticType,? extends SummaryType> summarizer) Creates a new instance of SupervisedLearnerExperiment.
OnlineLearnerValidationExperiment(PerformanceEvaluator<? super LearnedType,? super java.util.Collection<? extends DataType>,? extends StatisticType> performanceEvaluator, Summarizer<? super StatisticType,? extends SummaryType> summarizer) Creates a new instance of IncrementalLearnerValidationExperiment.
ParallelLearnerValidationExperiment(ValidationFoldCreator<InputDataType,FoldDataType> foldCreator, PerformanceEvaluator<? super LearnedType,? super java.util.Collection<? extends FoldDataType>,? extends StatisticType> performanceEvaluator, Summarizer<? super StatisticType,? extends SummaryType> summarizer) Creates a new instance of ParallelLearnerValidationExperiment.
SupervisedLearnerComparisonExperiment(ValidationFoldCreator<InputOutputPair<InputType,OutputType>,InputOutputPair<InputType,OutputType>> foldCreator, PerformanceEvaluator<? super Evaluator<? super InputType,OutputType>,? super java.util.Collection<? extends InputOutputPair<InputType,OutputType>>,? extends StatisticType> performanceEvaluator, NullHypothesisEvaluator<java.util.Collection<? extends StatisticType>> statisticalTest, Summarizer<? super StatisticType,? extends SummaryType> summarizer) Creates a new instance of SupervisedLearnerComparisonExperiment.
SupervisedLearnerValidationExperiment(ValidationFoldCreator<InputOutputPair<InputType,OutputType>,InputOutputPair<InputType,OutputType>> foldCreator, PerformanceEvaluator<? super Evaluator<? super InputType,? extends OutputType>,? super java.util.Collection<? extends InputOutputPair<InputType,OutputType>>,? extends StatisticType> performanceEvaluator, Summarizer<? super StatisticType,? extends SummaryType> summarizer) Creates a new instance of SupervisedLearnerValidationExperiment.

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

Subinterfaces of Summarizer in gov.sandia.cognition.learning.function.cost

Modifier and Type	Interface and Description
interface	DifferentiableCostFunction The DifferentiableCostFunction is a cost function that can be differentiated.
interface	ParallelizableCostFunction Interface describing a cost function that can (largely) be computed in parallel.
interface	SupervisedCostFunction<InputType,TargetType> A type of CostFunction normally used in supervised-learning applications.

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

Modifier and Type	Class and Description
class	AbstractParallelizableCostFunction Partial implementation of the ParallelizableCostFunction
class	AbstractSupervisedCostFunction<InputType,TargetType> Partial implementation of SupervisedCostFunction
class	MeanL1CostFunction Cost function that evaluates the mean 1-norm error (absolute value of difference) weighted by a sample "weight" that is embedded in each sample.
class	MeanSquaredErrorCostFunction The MeanSquaredErrorCostFunction implements a cost function for functions that take as input a vector and return a vector.
class	ParallelizedCostFunctionContainer A cost function that automatically splits a ParallelizableCostFunction across multiple cores/processors to speed up computation.
class	SumSquaredErrorCostFunction This is the sum-squared error cost function

Uses of Summarizer in gov.sandia.cognition.learning.function.summarizer

Classes in gov.sandia.cognition.learning.function.summarizer that implement Summarizer

Modifier and Type	Class and Description
class	MostFrequentSummarizer<DataType> Summarizes a set of values by returning the most frequent value.

Uses of Summarizer in gov.sandia.cognition.learning.performance

Classes in gov.sandia.cognition.learning.performance that implement Summarizer

Modifier and Type	Class and Description
class	AbstractSupervisedPerformanceEvaluator<InputType,TargetType,EstimateType,ResultType> The AbstractSupervisedPerformanceEvaluator class contains an abstract implementation of the SupervisedPerformanceEvaluator class.
class	MeanAbsoluteErrorEvaluator<InputType> The MeanAbsoluteError class implements a method for computing the performance of a supervised learner for a scalar function by the mean absolute value between the target and estimated outputs.
class	MeanSquaredErrorEvaluator<InputType> The MeanSquaredError class implements the method for computing the performance of a supervised learner for a scalar function by the mean squared between the target and estimated outputs.
class	MeanZeroOneErrorEvaluator<InputType,DataType> The MeanZeroOneErrorEvaluator class implements a method for computing the performance of a supervised learner by the mean number of incorrect values between the target and estimated outputs.
class	RootMeanSquaredErrorEvaluator<InputType> The RootMeanSquaredErrorEvaluator class implements a method for computing the performance of a supervised learner for a scalar function by the root mean squared error (RMSE or RSE) between the target and estimated outputs.

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

Classes in gov.sandia.cognition.learning.performance.categorization that implement Summarizer

Modifier and Type	Class and Description
class	ConfusionMatrixPerformanceEvaluator<InputType,CategoryType> A performance evaluator that builds a confusion matrix.
static class	DefaultBinaryConfusionMatrix.ActualPredictedPairSummarizer A confusion matrix summarizer that summarizes actual-predicted pairs.
static class	DefaultBinaryConfusionMatrix.CombineSummarizer A confusion matrix summarizer that adds together confusion matrices.
static class	DefaultBinaryConfusionMatrix.PerformanceEvaluator<InputType> An implementation of the SupervisedPerformanceEvaluator interface for creating a DefaultBinaryConfusionMatrix.
static class	DefaultBinaryConfusionMatrixConfidenceInterval.Summary An implementation of the Summarizer interface for creating a ConfusionMatrixInterval
static class	DefaultConfusionMatrix.ActualPredictedPairSummarizer<CategoryType> A confusion matrix summarizer that summarizes actual-predicted pairs.
static class	DefaultConfusionMatrix.CombineSummarizer<CategoryType> A confusion matrix summarizer that adds together confusion matrices.

Uses of Summarizer in gov.sandia.cognition.math

Classes in gov.sandia.cognition.math that implement Summarizer

Modifier and Type	Class and Description
class	NumberAverager Returns an average (arithmetic mean) of a collection of Numbers
class	RingAverager<RingType extends Ring<RingType>> A type of Averager for Rings (Matrices, Vectors, ComplexNumbers).
class	WeightedNumberAverager Averages together given set of weighted values by adding up the weight times the value and then dividing by the total weight.
class	WeightedRingAverager<RingType extends Ring<RingType>> A type of Summarizer for Rings (Matrices, Vectors, ComplexNumbers).

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

Classes in gov.sandia.cognition.statistics.method that implement Summarizer

Modifier and Type	Class and Description
static class	StudentTConfidence.Summary An implementation of the Summarizer interface for creating a ConfidenceInterval