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## weka.clusterers
Class FarthestFirst

    java.lang.Object
      weka.clusterers.AbstractClusterer
          weka.clusterers.RandomizableClusterer
              weka.clusterers.FarthestFirst

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

    public class FarthestFirst

extends RandomizableClusterer
implements TechnicalInformationHandler

Cluster data using the FarthestFirst algorithm.
For more information see:
Hochbaum, Shmoys (1985). A best possible heuristic for the k-center problem. Mathematics of Operations Research. 10(2):180-184.
Sanjoy Dasgupta: Performance Guarantees for Hierarchical Clustering. In: 15th Annual Conference on Computational Learning Theory, 351-363, 2002.
Notes:
- works as a fast simple approximate clusterer
- modelled after SimpleKMeans, might be a useful initializer for it

BibTeX:

     @article{Hochbaum1985,
        author = {Hochbaum and Shmoys},
        journal = {Mathematics of Operations Research},
        number = {2},
        pages = {180-184},
        title = {A best possible heuristic for the k-center problem},
        volume = {10},
        year = {1985}
     }

     @inproceedings{Dasgupta2002,
        author = {Sanjoy Dasgupta},
        booktitle = {15th Annual Conference on Computational Learning Theory},
        pages = {351-363},
        publisher = {Springer},
        title = {Performance Guarantees for Hierarchical Clustering},
        year = {2002}
     }

Valid options are:

     -N <num>
      number of clusters. (default = 2).

     -S <num>
      Random number seed.
      (default 1)

Version:
  $Revision: 5538 $
Author:
  Bernhard Pfahringer (bernhard@cs.waikato.ac.nz)
See Also:
  `RandomizableClusterer`, Serialized Form

Constructor Summary
`FarthestFirst()`

Method Summary
`void` | `buildClusterer(Instances data)` Generates a clusterer.
`int` | `clusterInstance(Instance instance)` Classifies a given instance.
`Capabilities` | `getCapabilities()` Returns default capabilities of the clusterer.
`int` | `getNumClusters()` gets the number of clusters to generate
`java.lang.String[]` | `getOptions()` Gets the current settings of FarthestFirst
`java.lang.String` | `getRevision()` Returns the revision string.
`TechnicalInformation` | `getTechnicalInformation()` Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
`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
`getSeed, seedTipText, setSeed`

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

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

Constructor Detail

### FarthestFirst

    public FarthestFirst()

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing this clusterer

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

### getTechnicalInformation

    public TechnicalInformation getTechnicalInformation()

  Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

  Specified by:
    `getTechnicalInformation` in interface `TechnicalInformationHandler`
  Returns:
    the technical information about this class

### 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 `AbstractClusterer`
  Returns:
    the capabilities of this clusterer
  See Also:
    `Capabilities`

### buildClusterer

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

  Generates a clusterer. Has to initialize all fields of the clusterer that are not being set via options.

  Specified by:
    `buildClusterer` in interface `Clusterer`
  Specified by:
    `buildClusterer` in class `AbstractClusterer`
  Parameters:
    `data` - set of instances serving as training data
  Throws:
    `java.lang.Exception` - if the clusterer has not been generated successfully

### clusterInstance

    public int clusterInstance(Instance instance)
                        throws java.lang.Exception

  Classifies a given instance.

  Specified by:
    `clusterInstance` in interface `Clusterer`
  Overrides:
    `clusterInstance` in class `AbstractClusterer`
  Parameters:
    `instance` - the instance to be assigned to a cluster
  Returns:
    the number of the assigned cluster as an integer if the class is enumerated, otherwise the predicted value
  Throws:
    `java.lang.Exception` - if instance could not be classified successfully

### numberOfClusters

    public int numberOfClusters()
                         throws java.lang.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:
    `java.lang.Exception` - if number of clusters could not be returned successfully

### listOptions

    public java.util.Enumeration listOptions()

  Returns an enumeration describing the available options.

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

### numClustersTipText

    public java.lang.String numClustersTipText()

  Returns the tip text for this property

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

### setNumClusters

    public void setNumClusters(int n)
                        throws java.lang.Exception

  set the number of clusters to generate

  Parameters:
    `n` - the number of clusters to generate
  Throws:
    `java.lang.Exception` - if number of clusters is negative

### getNumClusters

    public int getNumClusters()

  gets the number of clusters to generate

  Returns:
    the number of clusters to generate

### setOptions

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

  Parses a given list of options.

  Valid options are:

       -N <num>
        number of clusters. (default = 2).

       -S <num>
        Random number seed.
        (default 1)

  Specified by:
    `setOptions` in interface `OptionHandler`
  Overrides:
    `setOptions` in class `RandomizableClusterer`
  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 FarthestFirst

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

### toString

    public java.lang.String toString()

  return a string describing this clusterer

  Overrides:
    `toString` in class `java.lang.Object`
  Returns:
    a description of the clusterer as a string

### getRevision

    public java.lang.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(java.lang.String[] argv)

  Main method for testing this class.

  Parameters:
    `argv` - should contain the following arguments:

    -t training file [-N number of clusters]

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