Skip navigation links
B C D G I K L M N O R S T U W X 

B

binValueTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
buildClusterer(Instances) - Method in class weka.clusterers.XMeans
Generates the X-Means clusterer.

C

checkForNominalAttributes(Instances) - Method in class weka.clusterers.XMeans
Checks for nominal attributes in the dataset.
clusterInstance(Instance) - Method in class weka.clusterers.XMeans
Classifies a given instance.
cutOffFactorTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.

D

D_CONVCHCLOSER - Static variable in class weka.clusterers.XMeans
have a closer look at converge children.
D_CURR - Static variable in class weka.clusterers.XMeans
for current debug.
D_FOLLOWSPLIT - Static variable in class weka.clusterers.XMeans
follows the splitting of the centers.
D_GENERAL - Static variable in class weka.clusterers.XMeans
general debugging.
D_ITERCOUNT - Static variable in class weka.clusterers.XMeans
follow iterations.
D_KDTREE - Static variable in class weka.clusterers.XMeans
check on kdtree.
D_METH_MISUSE - Static variable in class weka.clusterers.XMeans
functions were maybe misused.
D_PRINTCENTERS - Static variable in class weka.clusterers.XMeans
print the centers.
D_RANDOMVECTOR - Static variable in class weka.clusterers.XMeans
check on random vectors.
debugLevelTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
debugVectorsFileTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
distanceFTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.

G

getBinValue() - Method in class weka.clusterers.XMeans
Gets value that represents true in a new numeric attribute.
getCapabilities() - Method in class weka.clusterers.XMeans
Returns default capabilities of the clusterer.
getClusterCenters() - Method in class weka.clusterers.XMeans
Return the centers of the clusters as an Instances object
getCutOffFactor() - Method in class weka.clusterers.XMeans
Gets the cutoff factor.
getDebugLevel() - Method in class weka.clusterers.XMeans
Gets the debug level.
getDebugVectorsFile() - Method in class weka.clusterers.XMeans
Gets the file name for a file that has the random vectors stored.
getDistanceF() - Method in class weka.clusterers.XMeans
Gets the distance function.
getInputCenterFile() - Method in class weka.clusterers.XMeans
Gets the file to read the list of centers from.
getKDTree() - Method in class weka.clusterers.XMeans
Gets the KDTree class.
getMaxIterations() - Method in class weka.clusterers.XMeans
Gets the maximum number of iterations.
getMaxKMeans() - Method in class weka.clusterers.XMeans
Gets the maximum number of iterations in KMeans.
getMaxKMeansForChildren() - Method in class weka.clusterers.XMeans
Gets the maximum number of iterations in KMeans.
getMaxNumClusters() - Method in class weka.clusterers.XMeans
Gets the maximum number of clusters to generate.
getMinNumClusters() - Method in class weka.clusterers.XMeans
Gets the minimum number of clusters to generate.
getNextDebugVectorsInstance(Instances) - Method in class weka.clusterers.XMeans
Read an instance from debug vectors file.
getOptions() - Method in class weka.clusterers.XMeans
Gets the current settings of SimpleKMeans.
getOutputCenterFile() - Method in class weka.clusterers.XMeans
Gets the file to write the list of centers to.
getRevision() - Method in class weka.clusterers.XMeans
Returns the revision string.
getTechnicalInformation() - Method in class weka.clusterers.XMeans
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getUseKDTree() - Method in class weka.clusterers.XMeans
Gets whether the KDTree is used or not.
globalInfo() - Method in class weka.clusterers.XMeans
Returns a string describing this clusterer.

I

initDebugVectorsInput() - Method in class weka.clusterers.XMeans
Initialises the debug vector input.
inputCenterFileTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.

K

KDTreeTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.

L

listOptions() - Method in class weka.clusterers.XMeans
Returns an enumeration describing the available options.

M

m_CurrDebugFlag - Variable in class weka.clusterers.XMeans
Flag: I'm debugging.
main(String[]) - Static method in class weka.clusterers.XMeans
Main method for testing this class.
maxIterationsTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
maxKMeansForChildrenTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
maxKMeansTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
maxNumClustersTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
minNumClustersTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.

N

numberOfClusters() - Method in class weka.clusterers.XMeans
Returns the number of clusters.

O

outputCenterFileTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.

R

R_HIGH - Static variable in class weka.clusterers.XMeans
Index in ranges for HIGH.
R_LOW - Static variable in class weka.clusterers.XMeans
Index in ranges for LOW.
R_WIDTH - Static variable in class weka.clusterers.XMeans
Index in ranges for WIDTH.

S

setBinValue(double) - Method in class weka.clusterers.XMeans
Sets the distance value between true and false of binary attributes.
setCutOffFactor(double) - Method in class weka.clusterers.XMeans
Sets a new cutoff factor.
setDebugLevel(int) - Method in class weka.clusterers.XMeans
Sets the debug level.
setDebugVectorsFile(File) - Method in class weka.clusterers.XMeans
Sets the file that has the random vectors stored.
setDistanceF(DistanceFunction) - Method in class weka.clusterers.XMeans
gets the "binary" distance value.
setInputCenterFile(File) - Method in class weka.clusterers.XMeans
Sets the file to read the list of centers from.
setKDTree(KDTree) - Method in class weka.clusterers.XMeans
Sets the KDTree class.
setMaxIterations(int) - Method in class weka.clusterers.XMeans
Sets the maximum number of iterations to perform.
setMaxKMeans(int) - Method in class weka.clusterers.XMeans
Set the maximum number of iterations to perform in KMeans.
setMaxKMeansForChildren(int) - Method in class weka.clusterers.XMeans
Sets the maximum number of iterations KMeans that is performed on the child centers.
setMaxNumClusters(int) - Method in class weka.clusterers.XMeans
Sets the maximum number of clusters to generate.
setMinNumClusters(int) - Method in class weka.clusterers.XMeans
Sets the minimum number of clusters to generate.
setOptions(String[]) - Method in class weka.clusterers.XMeans
Parses a given list of options.
setOutputCenterFile(File) - Method in class weka.clusterers.XMeans
Sets file to write the list of centers to.
setUseKDTree(boolean) - Method in class weka.clusterers.XMeans
Sets whether to use the KDTree or not.

T

toString() - Method in class weka.clusterers.XMeans
Return a string describing this clusterer.

U

useKDTreeTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.

W

weka.clusterers - package weka.clusterers
 

X

XMeans - Class in weka.clusterers
Cluster data using the X-means algorithm.

X-Means is K-Means extended by an Improve-Structure part In this part of the algorithm the centers are attempted to be split in its region.
XMeans() - Constructor for class weka.clusterers.XMeans
the default constructor.
B C D G I K L M N O R S T U W X 
Skip navigation links