public class CascadeSimpleKMeans
extends weka.clusterers.RandomizableClusterer
implements weka.clusterers.Clusterer, weka.core.TechnicalInformationHandler
Constructor and Description |
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CascadeSimpleKMeans() |
Modifier and Type | Method and Description |
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void |
buildClusterer(weka.core.Instances data) |
int |
clusterInstance(weka.core.Instance instance) |
java.lang.String |
distanceFunctionTipText() |
double[] |
distributionForInstance(weka.core.Instance instance) |
weka.core.Capabilities |
getCapabilities() |
weka.core.DistanceFunction |
getDistanceFunction() |
boolean |
getInitializeUsingKMeansPlusPlusMethod()
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).
|
int |
getMaxIterations() |
int |
getMaxNumClusters() |
int |
getMinNumClusters() |
java.lang.String[] |
getOptions()
Gets the current settings of SimpleKMeans.
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int |
getRestarts() |
java.lang.String |
getRevision()
Returns the revision string.
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weka.core.TechnicalInformation |
getTechnicalInformation() |
java.lang.String |
globalInfo()
Returns a string describing this clusterer.
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java.lang.String |
initializeUsingKMeansPlusPlusMethodTipText()
Returns the tip text for this property.
|
boolean |
isManuallySelectNumClusters() |
boolean |
isPrintDebug() |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options.
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static void |
main(java.lang.String[] args)
Main method for executing this class.
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java.lang.String |
manuallySelectNumClustersTipText() |
java.lang.String |
maxIterationsTipText() |
java.lang.String |
maxNumClustersTipText() |
java.lang.String |
minNumClustersTipText() |
int |
numberOfClusters() |
java.lang.String |
printDebugTipText() |
java.lang.String |
restartsTipText() |
void |
setDistanceFunction(weka.core.DistanceFunction distanceFunction) |
void |
setInitializeUsingKMeansPlusPlusMethod(boolean k)
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).
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void |
setManuallySelectNumClusters(boolean manuallySelectNumClusters) |
void |
setMaxIterations(int maxIterations) |
void |
setMaxNumClusters(int maxNumClusters) |
void |
setMinNumClusters(int minNumClusters) |
void |
setOptions(java.lang.String[] options)
Parses a given list of options.
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void |
setPrintDebug(boolean printDebug) |
void |
setRestarts(int restarts) |
java.lang.String |
toString() |
debugTipText, doNotCheckCapabilitiesTipText, forName, getDebug, getDoNotCheckCapabilities, makeCopies, makeCopy, postExecution, preExecution, run, runClusterer, setDebug, setDoNotCheckCapabilities
public weka.core.TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface weka.core.TechnicalInformationHandler
public java.lang.String toString()
toString
in class java.lang.Object
public java.lang.String globalInfo()
public void buildClusterer(weka.core.Instances data) throws java.lang.Exception
buildClusterer
in interface weka.clusterers.Clusterer
buildClusterer
in class weka.clusterers.AbstractClusterer
java.lang.Exception
public int clusterInstance(weka.core.Instance instance) throws java.lang.Exception
clusterInstance
in interface weka.clusterers.Clusterer
clusterInstance
in class weka.clusterers.AbstractClusterer
java.lang.Exception
public double[] distributionForInstance(weka.core.Instance instance) throws java.lang.Exception
distributionForInstance
in interface weka.clusterers.Clusterer
distributionForInstance
in class weka.clusterers.AbstractClusterer
java.lang.Exception
public int numberOfClusters() throws java.lang.Exception
numberOfClusters
in interface weka.clusterers.Clusterer
numberOfClusters
in class weka.clusterers.AbstractClusterer
java.lang.Exception
public weka.core.Capabilities getCapabilities()
getCapabilities
in interface weka.clusterers.Clusterer
getCapabilities
in interface weka.core.CapabilitiesHandler
getCapabilities
in class weka.clusterers.AbstractClusterer
public java.lang.String minNumClustersTipText()
public int getMinNumClusters()
public void setMinNumClusters(int minNumClusters)
public java.lang.String maxNumClustersTipText()
public int getMaxNumClusters()
public void setMaxNumClusters(int maxNumClusters)
public java.lang.String restartsTipText()
public int getRestarts()
public void setRestarts(int restarts)
public java.lang.String printDebugTipText()
public boolean isPrintDebug()
public void setPrintDebug(boolean printDebug)
public java.lang.String distanceFunctionTipText()
public weka.core.DistanceFunction getDistanceFunction()
public void setDistanceFunction(weka.core.DistanceFunction distanceFunction)
public java.lang.String maxIterationsTipText()
public int getMaxIterations()
public void setMaxIterations(int maxIterations)
public java.lang.String manuallySelectNumClustersTipText()
public boolean isManuallySelectNumClusters()
public void setManuallySelectNumClusters(boolean manuallySelectNumClusters)
public java.lang.String initializeUsingKMeansPlusPlusMethodTipText()
public void setInitializeUsingKMeansPlusPlusMethod(boolean k)
k
- true if the k-means++ method is to be used to select
initial cluster centers.public boolean getInitializeUsingKMeansPlusPlusMethod()
public java.util.Enumeration listOptions()
listOptions
in interface weka.core.OptionHandler
listOptions
in class weka.clusterers.RandomizableClusterer
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-N <num> number of clusters. (default 2).
-P Initialize using the k-means++ method.
-V Display std. deviations for centroids.
-M Replace missing values with mean/mode.
-A <classname and options> Distance function to use. (default: weka.core.EuclideanDistance)
-I <num> Maximum number of iterations.
-O Preserve order of instances.
-fast Enables faster distance calculations, using cut-off values. Disables the calculation/output of squared errors/distances.
-S <num> Random number seed. (default 10)
setOptions
in interface weka.core.OptionHandler
setOptions
in class weka.clusterers.RandomizableClusterer
options
- the list of options as an array of stringsjava.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface weka.core.OptionHandler
getOptions
in class weka.clusterers.RandomizableClusterer
public java.lang.String getRevision()
getRevision
in interface weka.core.RevisionHandler
getRevision
in class weka.clusterers.AbstractClusterer
public static void main(java.lang.String[] args)
args
- use -h to list all parameters