B C D G I L M N P R S T W

B

buildClusterer(Instances) - Method in class weka.clusterers.CascadeSimpleKMeans

C

CascadeSimpleKMeans - Class in weka.clusterers

cascade simple k means, selects the best k according to calinski-harabasz criterion analogous to: http://cc.oulu.fi/~jarioksa/softhelp/vegan/html/cascadeKM.html see Calinski, T.

CascadeSimpleKMeans() - Constructor for class weka.clusterers.CascadeSimpleKMeans

clusterInstance(Instance) - Method in class weka.clusterers.CascadeSimpleKMeans

D

distanceFunctionTipText() - Method in class weka.clusterers.CascadeSimpleKMeans

distributionForInstance(Instance) - Method in class weka.clusterers.CascadeSimpleKMeans

G

getCapabilities() - Method in class weka.clusterers.CascadeSimpleKMeans

getDistanceFunction() - Method in class weka.clusterers.CascadeSimpleKMeans

getInitializeUsingKMeansPlusPlusMethod() - Method in class weka.clusterers.CascadeSimpleKMeans

Get whether to initialize using the probabilistic farthest first like method of the k-means++ algorithm (rather than the standard random selection of initial cluster centers).

getMaxIterations() - Method in class weka.clusterers.CascadeSimpleKMeans

getMaxNumClusters() - Method in class weka.clusterers.CascadeSimpleKMeans

getMinNumClusters() - Method in class weka.clusterers.CascadeSimpleKMeans

getOptions() - Method in class weka.clusterers.CascadeSimpleKMeans

Gets the current settings of SimpleKMeans.

getRestarts() - Method in class weka.clusterers.CascadeSimpleKMeans

getRevision() - Method in class weka.clusterers.CascadeSimpleKMeans

Returns the revision string.

getTechnicalInformation() - Method in class weka.clusterers.CascadeSimpleKMeans

globalInfo() - Method in class weka.clusterers.CascadeSimpleKMeans

Returns a string describing this clusterer.

I

initializeUsingKMeansPlusPlusMethodTipText() - Method in class weka.clusterers.CascadeSimpleKMeans

Returns the tip text for this property.

isManuallySelectNumClusters() - Method in class weka.clusterers.CascadeSimpleKMeans

isPrintDebug() - Method in class weka.clusterers.CascadeSimpleKMeans

L

listOptions() - Method in class weka.clusterers.CascadeSimpleKMeans

Returns an enumeration describing the available options.

M

main(String[]) - Static method in class weka.clusterers.CascadeSimpleKMeans

Main method for executing this class.

manuallySelectNumClustersTipText() - Method in class weka.clusterers.CascadeSimpleKMeans

maxIterationsTipText() - Method in class weka.clusterers.CascadeSimpleKMeans

maxNumClustersTipText() - Method in class weka.clusterers.CascadeSimpleKMeans

minNumClustersTipText() - Method in class weka.clusterers.CascadeSimpleKMeans

N

numberOfClusters() - Method in class weka.clusterers.CascadeSimpleKMeans

P

printDebugTipText() - Method in class weka.clusterers.CascadeSimpleKMeans

R

restartsTipText() - Method in class weka.clusterers.CascadeSimpleKMeans

S

setDistanceFunction(DistanceFunction) - Method in class weka.clusterers.CascadeSimpleKMeans

setInitializeUsingKMeansPlusPlusMethod(boolean) - Method in class weka.clusterers.CascadeSimpleKMeans

Set whether to initialize using the probabilistic farthest first like method of the k-means++ algorithm (rather than the standard random selection of initial cluster centers).

setManuallySelectNumClusters(boolean) - Method in class weka.clusterers.CascadeSimpleKMeans

setMaxIterations(int) - Method in class weka.clusterers.CascadeSimpleKMeans

setMaxNumClusters(int) - Method in class weka.clusterers.CascadeSimpleKMeans

setMinNumClusters(int) - Method in class weka.clusterers.CascadeSimpleKMeans

setOptions(String[]) - Method in class weka.clusterers.CascadeSimpleKMeans

Parses a given list of options.

setPrintDebug(boolean) - Method in class weka.clusterers.CascadeSimpleKMeans

setRestarts(int) - Method in class weka.clusterers.CascadeSimpleKMeans

T

toString() - Method in class weka.clusterers.CascadeSimpleKMeans

W

weka.clusterers - package weka.clusterers

B C D G I L M N P R S T W