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

Packages that use Summarizer
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
 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
 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
AbstractKNearestNeighbor(int k, DivergenceFunction<? super InputType,? super InputType> divergenceFunction, Summarizer<? super OutputType,? extends OutputType> averager)
          Creates a new instance of KNearestNeighbor
KNearestNeighborExhaustive.Learner(int k, DivergenceFunction<? super InputType,? super InputType> divergenceFunction, Summarizer<? super OutputType,OutputType> averager)
          Creates a new instance of Learner
KNearestNeighborExhaustive(int k, 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.Learner(int k, Metric<? super Vectorizable> divergenceFunction, Summarizer<? super OutputType,? extends OutputType> averager)
          Creates a new instance of Learner
KNearestNeighborKDTree.Learner(Summarizer<? super OutputType,? extends OutputType> averager)
          Creates a new instance of Learner.
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
 

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

Fields in gov.sandia.cognition.learning.experiment declared as Summarizer
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
 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
 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
LearnerComparisonExperiment(ValidationFoldCreator<InputDataType,FoldDataType> foldCreator, PerformanceEvaluator<? super LearnedType,Collection<? extends FoldDataType>,? extends StatisticType> performanceEvaluator, NullHypothesisEvaluator<Collection<? extends StatisticType>> statisticalTest, Summarizer<? super StatisticType,? extends SummaryType> summarizer)
          Creates a new instance of LearnerComparisonExperiment.
LearnerRepeatExperiment(int numTrials, PerformanceEvaluator<? super LearnedType,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,Collection<? extends FoldDataType>,? extends StatisticType> performanceEvaluator, Summarizer<? super StatisticType,? extends SummaryType> summarizer)
          Creates a new instance of SupervisedLearnerExperiment.
OnlineLearnerValidationExperiment(PerformanceEvaluator<? super LearnedType,? super 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,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>,Collection<? extends InputOutputPair<InputType,OutputType>>,? extends StatisticType> performanceEvaluator, NullHypothesisEvaluator<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>,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
 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
 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
 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
 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
 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
 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
static class StudentTConfidence.Summary
          An implementation of the Summarizer interface for creating a ConfidenceInterval