FilteredClusterer

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## weka.clusterers
Class FilteredClusterer

    java.lang.Object
      weka.clusterers.AbstractClusterer
          weka.clusterers.SingleClustererEnhancer
              weka.clusterers.FilteredClusterer

All Implemented Interfaces:
  java.io.Serializable, java.lang.Cloneable, Clusterer, CapabilitiesHandler, OptionHandler, RevisionHandler

    public class FilteredClusterer

extends SingleClustererEnhancer

Class for running an arbitrary clusterer on data that has been passed through an arbitrary filter. Like the clusterer, the structure of the filter is based exclusively on the training data and test instances will be processed by the filter without changing their structure.

Valid options are:

     -F <filter specification>
      Full class name of filter to use, followed
      by filter options.
      eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"
     (default: weka.filters.AllFilter)

     -W
      Full name of base clusterer.
      (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)

Based on code from the FilteredClassifier by Len Trigg.

Version:
  $Revision: 1.4 $
Author:
  Len Trigg (trigg@cs.waikato.ac.nz), FracPete (fracpete at waikato dot ac dot nz)
See Also:
  `FilteredClassifier`, Serialized Form

Constructor Summary
`FilteredClusterer()` Default constructor.

Method Summary
`void` | `buildClusterer(Instances data)` Build the clusterer on the filtered data.
`double[]` | `distributionForInstance(Instance instance)` Classifies a given instance after filtering.
`java.lang.String` | `filterTipText()` Returns the tip text for this property.
`Capabilities` | `getCapabilities()` Returns default capabilities of the clusterer.
`Filter` | `getFilter()` Gets the filter used.
`java.lang.String[]` | `getOptions()` Gets the current settings of the clusterer.
`java.lang.String` | `getRevision()` Returns the revision string.
`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[] args)` Main method for testing this class.
`void` | `setFilter(Filter filter)` Sets the filter.
`void` | `setOptions(java.lang.String[] options)` Parses a given list of options.
`java.lang.String` | `toString()` Output a representation of this clusterer.

Methods inherited from class weka.clusterers.SingleClustererEnhancer
`clustererTipText, getClusterer, numberOfClusters, setClusterer`

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`

Constructor Detail

### FilteredClusterer

    public FilteredClusterer()

  Default constructor.

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing this clusterer.

  Returns:
    a description of the clusterer suitable for displaying in the explorer/experimenter gui

### listOptions

    public java.util.Enumeration listOptions()

  Returns an enumeration describing the available options.

  Specified by:
    `listOptions` in interface `OptionHandler`
  Overrides:
    `listOptions` in class `SingleClustererEnhancer`
  Returns:
    an enumeration of all the available options.

### setOptions

    public void setOptions(java.lang.String[] options)
                    throws java.lang.Exception

  Parses a given list of options.

  Valid options are:

       -F <filter specification>
        Full class name of filter to use, followed
        by filter options.
        eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"
       (default: weka.filters.AllFilter)

       -W
        Full name of base clusterer.
        (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`
  Overrides:
    `setOptions` in class `SingleClustererEnhancer`
  Parameters:
    `options` - the list of options as an array of strings
  Throws:
    `java.lang.Exception` - if an option is not supported

### getOptions

    public java.lang.String[] getOptions()

  Gets the current settings of the clusterer.

  Specified by:
    `getOptions` in interface `OptionHandler`
  Overrides:
    `getOptions` in class `SingleClustererEnhancer`
  Returns:
    an array of strings suitable for passing to setOptions

### filterTipText

    public java.lang.String filterTipText()

  Returns the tip text for this property.

  Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui

### setFilter

    public void setFilter(Filter filter)

  Sets the filter.

  Parameters:
    `filter` - the filter with all options set.

### getFilter

    public Filter getFilter()

  Gets the filter used.

  Returns:
    the filter

### getCapabilities

    public Capabilities getCapabilities()

  Returns default capabilities of the clusterer.

  Specified by:
    `getCapabilities` in interface `Clusterer`
  Specified by:
    `getCapabilities` in interface `CapabilitiesHandler`
  Overrides:
    `getCapabilities` in class `SingleClustererEnhancer`
  Returns:
    the capabilities of this clusterer
  See Also:
    `Capabilities`

### buildClusterer

    public void buildClusterer(Instances data)
                        throws java.lang.Exception

  Build the clusterer on the filtered data.

  Specified by:
    `buildClusterer` in interface `Clusterer`
  Specified by:
    `buildClusterer` in class `AbstractClusterer`
  Parameters:
    `data` - the training data
  Throws:
    `java.lang.Exception` - if the clusterer could not be built successfully

### distributionForInstance

    public double[] distributionForInstance(Instance instance)
                                     throws java.lang.Exception

  Classifies a given instance after filtering.

  Specified by:
    `distributionForInstance` in interface `Clusterer`
  Overrides:
    `distributionForInstance` in class `AbstractClusterer`
  Parameters:
    `instance` - the instance to be classified
  Returns:
    the class distribution for the given instance
  Throws:
    `java.lang.Exception` - if instance could not be classified successfully

### toString

    public java.lang.String toString()

  Output a representation of this clusterer.

  Overrides:
    `toString` in class `java.lang.Object`
  Returns:
    a representation of this clusterer

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Returns:
    the revision

### main

    public static void main(java.lang.String[] args)

  Main method for testing this class.

  Parameters:
    `args` - the commandline options, use "-h" for help

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