Uses of Interface
gov.sandia.cognition.learning.performance.PerformanceEvaluator

Packages that use PerformanceEvaluator
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.performance Provides performance measures. 
gov.sandia.cognition.learning.performance.categorization Provides performance measures for categorizers. 
 

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

Classes in gov.sandia.cognition.learning.experiment that implement PerformanceEvaluator
 class LearnerRepeatExperiment<InputDataType,LearnedType,StatisticType,SummaryType>
          Runs an experiment where the same learner is evaluated multiple times on the same data.
 class LearnerValidationExperiment<InputDataType,FoldDataType,LearnedType,StatisticType,SummaryType>
          The LearnerValidationExperiment class implements an experiment where a supervised machine learning algorithm is evaluated by applying it to a set of folds created from a given set of data.
 class OnlineLearnerValidationExperiment<DataType,LearnedType,StatisticType,SummaryType>
          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.
 class ParallelLearnerValidationExperiment<InputDataType,FoldDataType,LearnedType,StatisticType,SummaryType>
          Parallel version of the LearnerValidationExperiment class that executes the validations experiments across available cores and hyperthreads.
 class SupervisedLearnerValidationExperiment<InputType,OutputType,StatisticType,SummaryType>
          The SupervisedLearnerValidationExperiment class extends the LearnerValidationExperiment class to provide a easy way to create a learner validation experiment for supervised learning.
 

Fields in gov.sandia.cognition.learning.experiment declared as PerformanceEvaluator
protected  PerformanceEvaluator<? super LearnedType,Collection<? extends FoldDataType>,? extends StatisticType> LearnerComparisonExperiment.performanceEvaluator
          The evaluator to use to compute the performance of the learned object on each fold.
protected  PerformanceEvaluator<? super LearnedType,Collection<? extends InputDataType>,? extends StatisticType> LearnerRepeatExperiment.performanceEvaluator
          The evaluator to use to compute the performance of the learned object on each fold.
protected  PerformanceEvaluator<? super LearnedType,Collection<? extends FoldDataType>,? extends StatisticType> LearnerValidationExperiment.performanceEvaluator
          The evaluator to use to compute the performance of the learned object on each fold.
protected  PerformanceEvaluator<? super LearnedType,? super Collection<? extends DataType>,? extends StatisticType> OnlineLearnerValidationExperiment.performanceEvaluator
          The evaluator to use to compute the performance of the learned object on each fold.
 

Methods in gov.sandia.cognition.learning.experiment that return PerformanceEvaluator
 PerformanceEvaluator<? super LearnedType,Collection<? extends FoldDataType>,? extends StatisticType> LearnerComparisonExperiment.getPerformanceEvaluator()
          Gets the performance evaluator to apply to each fold.
 PerformanceEvaluator<? super LearnedType,Collection<? extends InputDataType>,? extends StatisticType> LearnerRepeatExperiment.getPerformanceEvaluator()
          Gets the performance evaluator to apply to each fold.
 PerformanceEvaluator<? super LearnedType,Collection<? extends FoldDataType>,? extends StatisticType> LearnerValidationExperiment.getPerformanceEvaluator()
          Gets the performance evaluator to apply to each fold.
 PerformanceEvaluator<? super LearnedType,? super Collection<? extends DataType>,? extends StatisticType> OnlineLearnerValidationExperiment.getPerformanceEvaluator()
          Gets the performance evaluator to apply to each fold.
 

Methods in gov.sandia.cognition.learning.experiment with parameters of type PerformanceEvaluator
 void OnlineLearnerValidationExperiment.setPerformanceEvaluator(PerformanceEvaluator<? super LearnedType,? super Collection<? extends DataType>,? extends StatisticType> performanceEvaluator)
          Sets the performance evaluator to apply to each fold.
 void LearnerComparisonExperiment.setPerformanceEvaluator(PerformanceEvaluator<? super LearnedType,Collection<? extends FoldDataType>,? extends StatisticType> performanceEvaluator)
          Sets the performance evaluator to apply to each fold.
 void LearnerValidationExperiment.setPerformanceEvaluator(PerformanceEvaluator<? super LearnedType,Collection<? extends FoldDataType>,? extends StatisticType> performanceEvaluator)
          Sets the performance evaluator to apply to each fold.
 void LearnerRepeatExperiment.setPerformanceEvaluator(PerformanceEvaluator<? super LearnedType,Collection<? extends InputDataType>,? extends StatisticType> performanceEvaluator)
          Sets the performance evaluator to apply to each fold.
 

Constructors in gov.sandia.cognition.learning.experiment with parameters of type PerformanceEvaluator
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 PerformanceEvaluator in gov.sandia.cognition.learning.function.cost
 

Subinterfaces of PerformanceEvaluator 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 PerformanceEvaluator
 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 PerformanceEvaluator in gov.sandia.cognition.learning.performance
 

Subinterfaces of PerformanceEvaluator in gov.sandia.cognition.learning.performance
 interface SupervisedPerformanceEvaluator<InputType,TargetType,EstimateType,ResultType>
          The SupervisedPerformanceEvaluator interface extends the PerformanceEvaluator interface for performance evaluations of supervised machine learning algorithms where the target type is evaluated against the estimated type produced by the evaluator.
 

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

Classes in gov.sandia.cognition.learning.performance.categorization that implement PerformanceEvaluator
 class ConfusionMatrixPerformanceEvaluator<InputType,CategoryType>
          A performance evaluator that builds a confusion matrix.
static class DefaultBinaryConfusionMatrix.PerformanceEvaluator<InputType>
          An implementation of the SupervisedPerformanceEvaluator interface for creating a DefaultBinaryConfusionMatrix.