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## weka.classifiers.meta
Class ClassificationViaClustering

    java.lang.Object
      weka.classifiers.Classifier
          weka.classifiers.meta.ClassificationViaClustering

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

    public class ClassificationViaClustering

extends Classifier

A simple meta-classifier that uses a clusterer for classification. For cluster algorithms that use a fixed number of clusterers, like SimpleKMeans, the user has to make sure that the number of clusters to generate are the same as the number of class labels in the dataset in order to obtain a useful model.
Note: at prediction time, a missing value is returned if no cluster is found for the instance.
The code is based on the 'clusters to classes' functionality of the weka.clusterers.ClusterEvaluation class by Mark Hall.

Valid options are:

     -D
      If set, classifier is run in debug mode and
      may output additional info to the console

     -W
      Full name of 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)

Version:
  $Revision: 1.5 $
Author:
  fracpete (fracpete at waikato dot ac dot nz)
See Also:
  Serialized Form

Constructor Summary
`ClassificationViaClustering()` default constructor

Method Summary
`void` | `buildClassifier(Instances data)` builds the classifier
`double` | `classifyInstance(Instance instance)` Classifies the given test instance.
`java.lang.String` | `clustererTipText()` Returns the tip text for this property
`Capabilities` | `getCapabilities()` Returns default capabilities of the classifier.
`Clusterer` | `getClusterer()` Get the clusterer used as the base learner.
`java.lang.String[]` | `getOptions()` returns the options of the current setup
`java.lang.String` | `getRevision()` Returns the revision string.
`java.lang.String` | `globalInfo()` Returns a string describing classifier
`java.util.Enumeration` | `listOptions()` Gets an enumeration describing the available options.
`static void` | `main(java.lang.String[] args)` Runs the classifier with the given options
`void` | `setClusterer(Clusterer value)` Set the base clusterer.
`void` | `setOptions(java.lang.String[] options)` Parses the options for this object.
`java.lang.String` | `toString()` Returns a string representation of the classifier.

Methods inherited from class weka.classifiers.Classifier
`debugTipText, distributionForInstance, forName, getDebug, makeCopies, makeCopy, setDebug`

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

Constructor Detail

### ClassificationViaClustering

    public ClassificationViaClustering()

  default constructor

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing classifier

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

### listOptions

    public java.util.Enumeration listOptions()

  Gets an enumeration describing the available options.

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

### getOptions

    public java.lang.String[] getOptions()

  returns the options of the current setup

  Specified by:
    `getOptions` in interface `OptionHandler`
  Overrides:
    `getOptions` in class `Classifier`
  Returns:
    the current options

### setOptions

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

  Parses the options for this object.

  Valid options are:

       -D
        If set, classifier is run in debug mode and
        may output additional info to the console

       -W
        Full name of 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 `Classifier`
  Parameters:
    `options` - the options to use
  Throws:
    `java.lang.Exception` - if setting of options fails

### clustererTipText

    public java.lang.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 value)

  Set the base clusterer.

  Parameters:
    `value` - the clusterer to use.

### getClusterer

    public Clusterer getClusterer()

  Get the clusterer used as the base learner.

  Returns:
    the current clusterer

### classifyInstance

    public double classifyInstance(Instance instance)
                            throws java.lang.Exception

  Classifies the given test instance.

  Overrides:
    `classifyInstance` in class `Classifier`
  Parameters:
    `instance` - the instance to be classified
  Returns:
    the predicted most likely class for the instance or Instance.missingValue() if no prediction is made
  Throws:
    `java.lang.Exception` - if an error occurred during the prediction

### getCapabilities

    public Capabilities getCapabilities()

  Returns default capabilities of the classifier.

  Specified by:
    `getCapabilities` in interface `CapabilitiesHandler`
  Overrides:
    `getCapabilities` in class `Classifier`
  Returns:
    the capabilities of this classifier
  See Also:
    `Capabilities`

### buildClassifier

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

  builds the classifier

  Specified by:
    `buildClassifier` in class `Classifier`
  Parameters:
    `data` - the training instances
  Throws:
    `java.lang.Exception` - if something goes wrong

### toString

    public java.lang.String toString()

  Returns a string representation of the classifier.

  Overrides:
    `toString` in class `java.lang.Object`
  Returns:
    a string representation of the classifier.

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Specified by:
    `getRevision` in interface `RevisionHandler`
  Overrides:
    `getRevision` in class `Classifier`
  Returns:
    the revision

### main

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

  Runs the classifier with the given options

  Parameters:
    `args` - the commandline options

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