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java.lang.Objectweka.clusterers.Clusterer
weka.clusterers.RandomizableClusterer
weka.clusterers.SimpleKMeans
public class SimpleKMeans
Cluster data using the k means algorithm
Valid options are:-N <num> number of clusters. (default 2).
-S <num> Random number seed. (default 10)
RandomizableClusterer
,
Serialized FormConstructor Summary | |
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SimpleKMeans()
the default constructor |
Method Summary | |
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void |
buildClusterer(Instances data)
Generates a clusterer. |
int |
clusterInstance(Instance instance)
Classifies a given instance. |
Capabilities |
getCapabilities()
Returns default capabilities of the clusterer. |
Instances |
getClusterCentroids()
Gets the the cluster centroids |
int[][][] |
getClusterNominalCounts()
Returns for each cluster the frequency counts for the values of each nominal attribute |
int[] |
getClusterSizes()
Gets the number of instances in each cluster |
Instances |
getClusterStandardDevs()
Gets the standard deviations of the numeric attributes in each cluster |
int |
getNumClusters()
gets the number of clusters to generate |
java.lang.String[] |
getOptions()
Gets the current settings of SimpleKMeans |
double |
getSquaredError()
Gets the squared error for all clusters |
java.lang.String |
globalInfo()
Returns a string describing this clusterer |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options. |
static void |
main(java.lang.String[] argv)
Main method for testing this class. |
int |
numberOfClusters()
Returns the number of clusters. |
java.lang.String |
numClustersTipText()
Returns the tip text for this property |
void |
setNumClusters(int n)
set the number of clusters to generate |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
java.lang.String |
toString()
return a string describing this clusterer |
Methods inherited from class weka.clusterers.RandomizableClusterer |
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getSeed, seedTipText, setSeed |
Methods inherited from class weka.clusterers.Clusterer |
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distributionForInstance, forName, makeCopies, makeCopy |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public SimpleKMeans()
Method Detail |
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public java.lang.String globalInfo()
public Capabilities getCapabilities()
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class Clusterer
Capabilities
public void buildClusterer(Instances data) throws java.lang.Exception
buildClusterer
in class Clusterer
data
- set of instances serving as training data
java.lang.Exception
- if the clusterer has not been
generated successfullypublic int clusterInstance(Instance instance) throws java.lang.Exception
clusterInstance
in class Clusterer
instance
- the instance to be assigned to a cluster
java.lang.Exception
- if instance could not be classified
successfullypublic int numberOfClusters() throws java.lang.Exception
numberOfClusters
in class Clusterer
java.lang.Exception
- if number of clusters could not be returned
successfullypublic java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class RandomizableClusterer
public java.lang.String numClustersTipText()
public void setNumClusters(int n) throws java.lang.Exception
setNumClusters
in interface NumberOfClustersRequestable
n
- the number of clusters to generate
java.lang.Exception
- if number of clusters is negativepublic int getNumClusters()
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-N <num> number of clusters. (default 2).
-S <num> Random number seed. (default 10)
setOptions
in interface OptionHandler
setOptions
in class RandomizableClusterer
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class RandomizableClusterer
public java.lang.String toString()
toString
in class java.lang.Object
public Instances getClusterCentroids()
public Instances getClusterStandardDevs()
public int[][][] getClusterNominalCounts()
public double getSquaredError()
public int[] getClusterSizes()
public static void main(java.lang.String[] argv)
argv
- should contain the following arguments: -t training file [-N number of clusters]
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