public class EM extends RandomizableDensityBasedClusterer implements NumberOfClustersRequestable, WeightedInstancesHandler
-N <num> number of clusters. If omitted or -1 specified, then cross validation is used to select the number of clusters.
-I <num> max iterations. (default 100)
-V verbose.
-M <num> minimum allowable standard deviation for normal density computation (default 1e-6)
-O Display model in old format (good when there are many clusters)
-S <num> Random number seed. (default 100)
Constructor and Description |
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EM()
Constructor.
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Modifier and Type | Method and Description |
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void |
buildClusterer(Instances data)
Generates a clusterer.
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double[] |
clusterPriors()
Returns the cluster priors.
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java.lang.String |
debugTipText()
Returns the tip text for this property
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java.lang.String |
displayModelInOldFormatTipText()
Returns the tip text for this property
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Capabilities |
getCapabilities()
Returns default capabilities of the clusterer (i.e., the ones of
SimpleKMeans).
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double[][][] |
getClusterModelsNumericAtts()
Return the normal distributions for the cluster models
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double[] |
getClusterPriors()
Return the priors for the clusters
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boolean |
getDebug()
Get debug mode
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boolean |
getDisplayModelInOldFormat()
Get whether to display model output in the old, original
format.
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int |
getMaxIterations()
Get the maximum number of iterations
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double |
getMinStdDev()
Get the minimum allowable standard deviation.
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int |
getNumClusters()
Get the number of clusters
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java.lang.String[] |
getOptions()
Gets the current settings of EM.
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java.lang.String |
getRevision()
Returns the revision string.
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java.lang.String |
globalInfo()
Returns a string describing this clusterer
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java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options.
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double[] |
logDensityPerClusterForInstance(Instance inst)
Computes the log of the conditional density (per cluster) for a given instance.
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static void |
main(java.lang.String[] argv)
Main method for testing this class.
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java.lang.String |
maxIterationsTipText()
Returns the tip text for this property
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java.lang.String |
minStdDevTipText()
Returns the tip text for this property
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int |
numberOfClusters()
Returns the number of clusters.
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java.lang.String |
numClustersTipText()
Returns the tip text for this property
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void |
setDebug(boolean v)
Set debug mode - verbose output
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void |
setDisplayModelInOldFormat(boolean d)
Set whether to display model output in the old, original
format.
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void |
setMaxIterations(int i)
Set the maximum number of iterations to perform
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void |
setMinStdDev(double m)
Set the minimum value for standard deviation when calculating
normal density.
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void |
setMinStdDevPerAtt(double[] m) |
void |
setNumClusters(int n)
Set the number of clusters (-1 to select by CV).
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void |
setOptions(java.lang.String[] options)
Parses a given list of options.
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java.lang.String |
toString()
Outputs the generated clusters into a string.
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getSeed, seedTipText, setSeed
distributionForInstance, logDensityForInstance, logJointDensitiesForInstance, makeCopies
clusterInstance, forName, makeCopies, makeCopy
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
clusterInstance
public java.lang.String globalInfo()
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class RandomizableDensityBasedClusterer
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-N <num> number of clusters. If omitted or -1 specified, then cross validation is used to select the number of clusters.
-I <num> max iterations. (default 100)
-V verbose.
-M <num> minimum allowable standard deviation for normal density computation (default 1e-6)
-O Display model in old format (good when there are many clusters)
-S <num> Random number seed. (default 100)
setOptions
in interface OptionHandler
setOptions
in class RandomizableDensityBasedClusterer
options
- the list of options as an array of stringsjava.lang.Exception
- if an option is not supportedpublic java.lang.String displayModelInOldFormatTipText()
public void setDisplayModelInOldFormat(boolean d)
d
- true if model ouput is to be shown in the old formatpublic boolean getDisplayModelInOldFormat()
public java.lang.String minStdDevTipText()
public void setMinStdDev(double m)
m
- minimum value for standard deviationpublic void setMinStdDevPerAtt(double[] m)
public double getMinStdDev()
public java.lang.String numClustersTipText()
public void setNumClusters(int n) throws java.lang.Exception
setNumClusters
in interface NumberOfClustersRequestable
n
- the number of clustersjava.lang.Exception
- if n is 0public int getNumClusters()
public java.lang.String maxIterationsTipText()
public void setMaxIterations(int i) throws java.lang.Exception
i
- the number of iterationsjava.lang.Exception
- if i is less than 1public int getMaxIterations()
public java.lang.String debugTipText()
public void setDebug(boolean v)
v
- true for verbose outputpublic boolean getDebug()
public java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class RandomizableDensityBasedClusterer
public double[][][] getClusterModelsNumericAtts()
double[][][]
valuepublic double[] getClusterPriors()
double[]
valuepublic java.lang.String toString()
toString
in class java.lang.Object
public int numberOfClusters() throws java.lang.Exception
numberOfClusters
in interface Clusterer
numberOfClusters
in class AbstractClusterer
java.lang.Exception
- if number of clusters could not be returned
successfullypublic Capabilities getCapabilities()
getCapabilities
in interface Clusterer
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class AbstractClusterer
Capabilities
public void buildClusterer(Instances data) throws java.lang.Exception
buildClusterer
in interface Clusterer
buildClusterer
in class AbstractClusterer
data
- set of instances serving as training datajava.lang.Exception
- if the clusterer has not been
generated successfullypublic double[] clusterPriors()
clusterPriors
in interface DensityBasedClusterer
clusterPriors
in class AbstractDensityBasedClusterer
public double[] logDensityPerClusterForInstance(Instance inst) throws java.lang.Exception
logDensityPerClusterForInstance
in interface DensityBasedClusterer
logDensityPerClusterForInstance
in class AbstractDensityBasedClusterer
inst
- the instance to compute the density forjava.lang.Exception
- if the density could not be computed
successfullypublic java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class AbstractClusterer
public static void main(java.lang.String[] argv)
argv
- should contain the following arguments: -t training file [-T test file] [-N number of clusters] [-S random seed]