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S

score(Dataset[]) - Method in class ristretto.jmltools.clustering.evaluation.DaviesBouldin

Return the score the current clusterer obtains on the dataset

score(Dataset[]) - Method in class ristretto.jmltools.clustering.evaluation.DunnIndex

Return the score the current clusterer obtains on the dataset

score(Dataset[]) - Method in class ristretto.jmltools.clustering.evaluation.FarthestCentroids

Return the score the current clusterer obtains on the dataset

score(Dataset[]) - Method in class ristretto.jmltools.clustering.evaluation.MaxClusterDiameter

Return the score the current clusterer obtains on the dataset

score(Dataset[]) - Method in class ristretto.jmltools.clustering.evaluation.MinFarthestCentroid

Return the score the current clusterer obtains on the dataset

score(Dataset[]) - Method in class ristretto.jmltools.clustering.evaluation.OverallDeviation

Return the score the current clusterer obtains on the dataset

sensitivity(Map<Object, PerformanceMeasure>, Object) - Static method in class ristretto.jmltools.classification.evaluation.PerformanceIndexes

This method implements sensitivity of a classification.

sensitivity(Classifier, Dataset, Object) - Static method in class ristretto.jmltools.classification.evaluation.PerformanceIndexes

This method implements sensitivity of a classification.

separationIndexClass - Variable in class ristretto.problem.fs.subset.unsupervised.FSSubsetUnsupervisedProblem

Separation index

separationNormMethodName - Variable in class ristretto.problem.fs.subset.unsupervised.FSSubsetUnsupervisedProblem

Normalization factor for the separation index

setGenome(Object) - Method in class ristretto.problem.fs.subset.FSSubsetIndividual

Set the genome.

setObjectives(EvolutionState, double[]) - Method in class ristretto.ecjtools.LexicographicFitness

Set new values for the objectives

setup(EvolutionState, Parameter) - Method in class ristretto.ecjtools.CoevolutionaryStatistics

Set up the problem by reading it from the parameters stored in state, built off of the parameter base base.

setup(EvolutionState, Parameter) - Method in class ristretto.ecjtools.LexicographicFitness

Set up.

setup(EvolutionState, Parameter) - Method in class ristretto.ecjtools.MultiObjectiveStatistics

Set up the statistics by reading it from the parameters stored in state, built off of the parameter base base.

setup(EvolutionState, Parameter) - Method in class ristretto.problem.fs.subset.breed.FSSubsetCrossoverPipeline

Set up the pipeline.

setup(EvolutionState, Parameter) - Method in class ristretto.problem.fs.subset.FSSubsetIndividual

Set up this individual.

setup(EvolutionState, Parameter) - Method in class ristretto.problem.fs.subset.FSSubsetProblem

Set up the problem by reading it from the parameters stored in state, built off of the parameter base base.

setup(EvolutionState, Parameter) - Method in class ristretto.problem.fs.subset.FSSubsetSpecies

Set up the species.

setup(EvolutionState, Parameter) - Method in class ristretto.problem.fs.subset.supervised.FSSubsetSupervisedCoevolutionaryProblem

Sets up the problem by reading it from the parameters stored in state, built off of the parameter base base.

setup(EvolutionState, Parameter) - Method in class ristretto.problem.fs.subset.supervised.FSSubsetSupervisedProblem

Sets up the problem by reading it from the parameters stored in state, built off of the parameter base base.

setup(EvolutionState, Parameter) - Method in class ristretto.problem.fs.subset.unsupervised.FSSubsetUnsupervisedProblem

Set up the problem by reading it from the parameters stored in state, built off of the parameter base base

setup(EvolutionState, Parameter) - Method in class tests.testCoevolution.CoevolutionaryMaxOnes

Sets up the problem by reading it from the parameters stored in state, built off of the parameter base base.

setup(EvolutionState, Parameter) - Method in class tests.testLibSVM.TestLibSVM

Set up the problem by reading it from the parameters stored in state, built off of the parameter base base.

silentFront - Variable in class ristretto.ecjtools.MultiObjectiveStatistics

Silent front

size() - Method in class ristretto.problem.fs.subset.FSSubsetIndividual

Return the number of selected features

specificity(Map<Object, PerformanceMeasure>, Object) - Static method in class ristretto.jmltools.classification.evaluation.PerformanceIndexes

This method implements specificity of a classification.

specificity(Classifier, Dataset, Object) - Static method in class ristretto.jmltools.classification.evaluation.PerformanceIndexes

This method implements specificity of a classification.

split(Dataset, double) - Static method in class ristretto.jmltools.MoreDatasetTools

Extracts a proportion of samples ramdomly from a original dataset and returns them as a new dataset.

stopCriterion - Variable in class ristretto.jmltools.clustering.LBG

Stop criterion

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