MakeDensityBasedClusterer (weka-stable 3.6.14 API)

java.lang.Object
- weka.clusterers.AbstractClusterer
- - weka.clusterers.AbstractDensityBasedClusterer
  - - weka.clusterers.MakeDensityBasedClusterer

All Implemented Interfaces:

Serializable, Cloneable, Clusterer, DensityBasedClusterer, NumberOfClustersRequestable, CapabilitiesHandler, OptionHandler, RevisionHandler, WeightedInstancesHandler
```
public class MakeDensityBasedClusterer
extends AbstractDensityBasedClusterer
implements NumberOfClustersRequestable, OptionHandler, WeightedInstancesHandler
```
Class for wrapping a Clusterer to make it return a distribution and density. Fits normal distributions and discrete distributions within each cluster produced by the wrapped clusterer. Supports the NumberOfClustersRequestable interface only if the wrapped Clusterer does.
Valid options are:
```
 -M <num>
  minimum allowable standard deviation for normal density computation 
  (default 1e-6)
```
```
 -W <clusterer name>
  Clusterer to wrap.
  (default weka.clusterers.SimpleKMeans)
```
```
 
 Options specific to clusterer weka.clusterers.SimpleKMeans:
 
```
```
 -N <num>
  number of clusters.
  (default 2).
```
```
 -V
  Display std. deviations for centroids.
 
```
```
 -M
  Replace missing values with mean/mode.
 
```
```
 -S <num>
  Random number seed.
  (default 10)
```
Options after "--" are passed on to the base clusterer.
Version:

$Revision: 5538 $

Author:

Richard Kirkby ([email protected]), Mark Hall ([email protected]), Eibe Frank ([email protected])

See Also:
Serialized Form

Constructor Summary

Constructors
Constructor and Description
`MakeDensityBasedClusterer()` Default constructor.
`MakeDensityBasedClusterer(Clusterer toWrap)` Contructs a MakeDensityBasedClusterer wrapping a given Clusterer.

Method Summary

Methods
Modifier and Type	Method and Description
`void`	`buildClusterer(Instances data)` Builds a clusterer for a set of instances.
`String`	`clustererTipText()` Returns the tip text for this property
`double[]`	`clusterPriors()` Returns the cluster priors.
`Capabilities`	`getCapabilities()` Returns default capabilities of the clusterer (i.e., of the wrapper clusterer).
`Clusterer`	`getClusterer()` Gets the clusterer being wrapped.
`double`	`getMinStdDev()` Get the minimum allowable standard deviation.
`String[]`	`getOptions()` Gets the current settings of the clusterer.
`String`	`getRevision()` Returns the revision string.
`String`	`globalInfo()` Returns a string describing classifier
`Enumeration`	`listOptions()` Returns an enumeration describing the available options..
`double[]`	`logDensityPerClusterForInstance(Instance inst)` Computes the log of the conditional density (per cluster) for a given instance.
`static void`	`main(String[] argv)` Main method for testing this class.
`String`	`minStdDevTipText()` Returns the tip text for this property
`int`	`numberOfClusters()` Returns the number of clusters.
`void`	`setClusterer(Clusterer toWrap)` Sets the clusterer to wrap.
`void`	`setMinStdDev(double m)` Set the minimum value for standard deviation when calculating normal density.
`void`	`setNumClusters(int n)` Set the number of clusters to generate.
`void`	`setOptions(String[] options)` Parses a given list of options.
`String`	`toString()` Returns a description of the clusterer.

Methods inherited from class weka.clusterers.AbstractDensityBasedClusterer
distributionForInstance, logDensityForInstance, logJointDensitiesForInstance, makeCopies

Methods inherited from class weka.clusterers.AbstractClusterer
clusterInstance, forName, makeCopies, makeCopy

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.clusterers.Clusterer
clusterInstance

- Constructor Detail
  - MakeDensityBasedClusterer
```
public MakeDensityBasedClusterer()
```
    Default constructor.
  - MakeDensityBasedClusterer
```
public MakeDensityBasedClusterer(Clusterer toWrap)
```
    Contructs a MakeDensityBasedClusterer wrapping a given Clusterer.
    
    Parameters:
    toWrap - the clusterer to wrap around
- Method Detail
  - globalInfo
```
public String globalInfo()
```
    Returns a string describing classifier
    
    Returns:
    a description suitable for displaying in the explorer/experimenter gui
  - setNumClusters
```
public void setNumClusters(int n)
                    throws Exception
```
    Set the number of clusters to generate.
    
    Specified by:
    
    setNumClusters in interface NumberOfClustersRequestable
    
    Parameters:
    n - the number of clusters to generate
    
    Throws:
    
    Exception - if the wrapped clusterer has not been set, or if the wrapped clusterer does not implement this facility.
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns default capabilities of the clusterer (i.e., of the wrapper clusterer).
    
    Specified by:
    
    getCapabilities in interface Clusterer
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class AbstractClusterer
    
    Returns:
    the capabilities of this clusterer
    See Also:
    Capabilities
  - buildClusterer
```
public void buildClusterer(Instances data)
                    throws Exception
```
    Builds a clusterer for a set of instances.
    
    Specified by:
    
    buildClusterer in interface Clusterer
    
    Specified by:
    
    buildClusterer in class AbstractClusterer
    
    Parameters:
    data - the instances to train the clusterer with
    
    Throws:
    
    Exception - if the clusterer hasn't been set or something goes wrong
  - clusterPriors
```
public double[] clusterPriors()
```
    Returns the cluster priors.
    
    Specified by:
    
    clusterPriors in interface DensityBasedClusterer
    
    Specified by:
    
    clusterPriors in class AbstractDensityBasedClusterer
    
    Returns:
    the cluster priors
  - logDensityPerClusterForInstance
```
public double[] logDensityPerClusterForInstance(Instance inst)
                                         throws Exception
```
    Computes the log of the conditional density (per cluster) for a given instance.
    
    Specified by:
    
    logDensityPerClusterForInstance in interface DensityBasedClusterer
    
    Specified by:
    
    logDensityPerClusterForInstance in class AbstractDensityBasedClusterer
    
    Parameters:
    inst - the instance to compute the density for
    
    Returns:
    an array containing the estimated densities
    
    Throws:
    
    Exception - if the density could not be computed successfully
  - numberOfClusters
```
public int numberOfClusters()
                     throws Exception
```
    Returns the number of clusters.
    
    Specified by:
    
    numberOfClusters in interface Clusterer
    
    Specified by:
    
    numberOfClusters in class AbstractClusterer
    
    Returns:
    the number of clusters generated for a training dataset.
    
    Throws:
    
    Exception - if number of clusters could not be returned successfully
  - toString
```
public String toString()
```
    Returns a description of the clusterer.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    a string containing a description of the clusterer
  - clustererTipText
```
public String clustererTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setClusterer
```
public void setClusterer(Clusterer toWrap)
```
    Sets the clusterer to wrap.
    
    Parameters:
    toWrap - the clusterer
  - getClusterer
```
public Clusterer getClusterer()
```
    Gets the clusterer being wrapped.
    
    Returns:
    the clusterer
  - minStdDevTipText
```
public String minStdDevTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setMinStdDev
```
public void setMinStdDev(double m)
```
    Set the minimum value for standard deviation when calculating normal density. Reducing this value can help prevent arithmetic overflow resulting from multiplying large densities (arising from small standard deviations) when there are many singleton or near singleton values.
    
    Parameters:
    m - minimum value for standard deviation
  - getMinStdDev
```
public double getMinStdDev()
```
    Get the minimum allowable standard deviation.
    
    Returns:
    the minumum allowable standard deviation
  - listOptions
```
public Enumeration listOptions()
```
    Returns an enumeration describing the available options..
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Returns:
    an enumeration of all the available options.
  - setOptions
```
public void setOptions(String[] options)
                throws Exception
```
    Parses a given list of options.
    Valid options are:
```
 -M <num>
  minimum allowable standard deviation for normal density computation 
  (default 1e-6)
```
```
 -W <clusterer name>
  Clusterer to wrap.
  (default weka.clusterers.SimpleKMeans)
```
```
 
 Options specific to clusterer weka.clusterers.SimpleKMeans:
 
```
```
 -N <num>
  number of clusters.
  (default 2).
```
```
 -V
  Display std. deviations for centroids.
 
```
```
 -M
  Replace missing values with mean/mode.
 
```
```
 -S <num>
  Random number seed.
  (default 10)
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Parameters:
    options - the list of options as an array of strings
    
    Throws:
    
    Exception - if an option is not supported
  - getOptions
```
public String[] getOptions()
```
    Gets the current settings of the clusterer.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Returns:
    an array of strings suitable for passing to setOptions()
  - getRevision
```
public String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class AbstractClusterer
    
    Returns:
    the revision
  - main
```
public static void main(String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    argv - the options

Class MakeDensityBasedClusterer

Constructor Summary

Method Summary

Methods inherited from class weka.clusterers.AbstractDensityBasedClusterer

Methods inherited from class weka.clusterers.AbstractClusterer

Methods inherited from class java.lang.Object

Methods inherited from interface weka.clusterers.Clusterer

Constructor Detail

MakeDensityBasedClusterer

MakeDensityBasedClusterer

Method Detail

globalInfo

setNumClusters

getCapabilities

buildClusterer

clusterPriors

logDensityPerClusterForInstance

numberOfClusters

toString

clustererTipText

setClusterer

getClusterer

minStdDevTipText

setMinStdDev

getMinStdDev

listOptions

setOptions

getOptions

getRevision

main