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D

data - Variable in class ristretto.problem.fs.subset.FSSubsetProblem

The dataset

DatasetSplitter - Class in ristretto.tools

Split a dataset into a training and test datasets given a test proportion, that is, the proportion of data reserved to the test dataset.

DatasetSplitter() - Constructor for class ristretto.tools.DatasetSplitter

DaviesBouldin - Class in ristretto.jmltools.clustering.evaluation

This class implements the CVI proposed by Davies and Bouldin in [1].

DaviesBouldin() - Constructor for class ristretto.jmltools.clustering.evaluation.DaviesBouldin

Construct a new evaluator that will use the Euclidean distance to measure the errors.

DaviesBouldin(DistanceMeasure) - Constructor for class ristretto.jmltools.clustering.evaluation.DaviesBouldin

Construct a new evaluator that will use the supplied distance metric to measure the errors

debug - Variable in class ristretto.problem.fs.subset.FSSubsetProblem

Whether to activate the debug logs

defaultBase() - Method in class ristretto.ecjtools.LexicographicFitness

Return the default parameter base.

defaultBase() - Method in class ristretto.problem.fs.subset.breed.FSSubsetCrossoverPipeline

Return the default parameter base.

defaultBase() - Method in class ristretto.problem.fs.subset.breed.FSSubsetMutationPipeline

Return the default parameter base.

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

Return the default parameter base.

defaultBase() - Method in class ristretto.problem.fs.subset.FSSubsetProblem

Return the default parameter base for this problem.

defaultBase() - Method in class ristretto.problem.fs.subset.FSSubsetSpecies

Return the default parameter base.

defaultBase() - Method in class ristretto.problem.fs.subset.supervised.FSSubsetSupervisedCoevolutionaryProblem

Returns the default base for this problem.

defaultBase() - Method in class ristretto.problem.fs.subset.supervised.FSSubsetSupervisedProblem

Return the default base for this problem.

defaultBase() - Method in class ristretto.problem.fs.subset.unsupervised.FSSubsetUnsupervisedProblem

Return the default base for this problem

defaultBase() - Method in class tests.testLibSVM.TestLibSVM

Return the default base for this problem

defaultClassifier - Static variable in class ristretto.problem.fs.subset.supervised.FSSubsetSupervisedProblem

Default classifier

defaultCrossover(EvolutionState, int, FSSubsetIndividual) - Method in class ristretto.problem.fs.subset.FSSubsetIndividual

Destructively crosses over the individual with another in some default manner.

defaultMutate(EvolutionState, int) - Method in class ristretto.problem.fs.subset.FSSubsetIndividual

Destructively mutates the individual in some default manner.

defaultNumberOfClusters - Static variable in class ristretto.jmltools.clustering.LBG

Default value for the number of centroids

defaultStopCriterion - Static variable in class ristretto.jmltools.clustering.LBG

Default value for the stop criterion

defaultThreshold - Static variable in class ristretto.ecjtools.LexicographicFitness

Default value for the similarity threshold

defaultValidationProp - Static variable in class ristretto.problem.fs.subset.supervised.FSSubsetSupervisedProblem

Default validation proportion

defaultValidationProp - Static variable in class tests.testLibSVM.TestLibSVM

Default validation proportion

directLDA(Dataset) - Static method in class ristretto.jmltools.MoreDatasetTools

Performs a projection of a given dataset with the directLDA algorithm.

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

Performs a projection of a given dataset with the directLDA algorithm [1].

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

Distortion of each cluster

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

Distance measure used in the algorithm, defaults to Euclidean distance.

DunnIndex - Class in ristretto.jmltools.clustering.evaluation

This class implements the CVI proposed by Dunn in [1].

DunnIndex() - Constructor for class ristretto.jmltools.clustering.evaluation.DunnIndex

Construct a new evaluator that will use the Euclidean distance to measure the errors.

DunnIndex(DistanceMeasure) - Constructor for class ristretto.jmltools.clustering.evaluation.DunnIndex

Construct a new evaluator that will use the supplied distance metric to measure the errors

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