Uses of Interface
weka.clusterers.DensityBasedClusterer
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Uses of DensityBasedClusterer in weka.clusterers
Modifier and TypeClassDescriptionclass
Abstract clustering model that produces (for each test instance) an estimate of the membership in each cluster (ie.class
Simple EM (expectation maximisation) class.
EM assigns a probability distribution to each instance which indicates the probability of it belonging to each of the clusters.class
Class for wrapping a Clusterer to make it return a distribution and density.class
Abstract utility class for handling settings common to randomizable clusterers.Modifier and TypeMethodDescriptionstatic DensityBasedClusterer[]
AbstractDensityBasedClusterer.makeCopies
(DensityBasedClusterer model, int num) Creates copies of the current clusterer.Modifier and TypeMethodDescriptionstatic double
ClusterEvaluation.crossValidateModel
(DensityBasedClusterer clusterer, Instances data, int numFolds, Random random) Perform a cross-validation for DensityBasedClusterer on a set of instances.static DensityBasedClusterer[]
AbstractDensityBasedClusterer.makeCopies
(DensityBasedClusterer model, int num) Creates copies of the current clusterer. -
Uses of DensityBasedClusterer in weka.experiment
Modifier and TypeMethodDescriptionDensityBasedClustererSplitEvaluator.getClusterer()
Get the value of clustererModifier and TypeMethodDescriptionvoid
DensityBasedClustererSplitEvaluator.setClusterer
(DensityBasedClusterer newClusterer) Sets the clusterer. -
Uses of DensityBasedClusterer in weka.filters.unsupervised.attribute
Modifier and TypeMethodDescriptionClusterMembership.getDensityBasedClusterer()
Get the clusterer used by this filterModifier and TypeMethodDescriptionvoid
ClusterMembership.setDensityBasedClusterer
(DensityBasedClusterer newClusterer) Set the clusterer for use in filtering