Class AbstractClusterer

Method Details

• buildClusterer

  public abstract void buildClusterer(Instances data) throws 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

  Parameters:

  data - set of instances serving as training data

  Throws:

  Exception - if the clusterer has not been generated successfully

• clusterInstance

  public int clusterInstance(Instance instance) throws Exception

  Classifies a given instance. Either this or distributionForInstance() needs to be implemented by subclasses.

  Specified by:

  clusterInstance in interface Clusterer

  Parameters:

  instance - the instance to be assigned to a cluster

  Returns:

  the number of the assigned cluster as an integer

  Throws:

  Exception - if instance could not be clustered successfully

• distributionForInstance

  public double[] distributionForInstance(Instance instance) throws Exception

  Predicts the cluster memberships for a given instance. Either this or clusterInstance() needs to be implemented by subclasses.

  Specified by:

  distributionForInstance in interface Clusterer

  Parameters:

  instance - the instance to be assigned a cluster.

  Returns:

  an array containing the estimated membership probabilities of the test instance in each cluster (this should sum to at most 1)

  Throws:

  Exception - if distribution could not be computed successfully

• numberOfClusters

  public abstract int numberOfClusters() throws Exception

  Returns the number of clusters.

  Specified by:

  numberOfClusters in interface Clusterer

  Returns:

  the number of clusters generated for a training dataset.

  Throws:

  Exception - if number of clusters could not be returned successfully

• forName

  public static Clusterer forName(String clustererName, String[] options) throws Exception

  Creates a new instance of a clusterer given it's class name and (optional) arguments to pass to it's setOptions method. If the clusterer implements OptionHandler and the options parameter is non-null, the clusterer will have it's options set.

  Parameters:

  clustererName - the fully qualified class name of the clusterer

  options - an array of options suitable for passing to setOptions. May be null.

  Returns:

  the newly created search object, ready for use.

  Throws:

  Exception - if the clusterer class name is invalid, or the options supplied are not acceptable to the clusterer.

• makeCopy

  public static Clusterer makeCopy(Clusterer model) throws Exception

  Creates a deep copy of the given clusterer using serialization.

  Parameters:

  model - the clusterer to copy

  Returns:

  a deep copy of the clusterer

  Throws:

  Exception - if an error occurs

• makeCopies

  public static Clusterer[] makeCopies(Clusterer model, int num) throws Exception

  Creates copies of the current clusterer. Note that this method now uses Serialization to perform a deep copy, so the Clusterer object must be fully Serializable. Any currently built model will now be copied as well.

  Parameters:

  model - an example clusterer to copy

  num - the number of clusterer copies to create.

  Returns:

  an array of clusterers.

  Throws:

  Exception - if an error occurs

• getCapabilities

  public Capabilities getCapabilities()

  Returns the Capabilities of this clusterer. Derived classifiers have to override this method to enable capabilities.

  Specified by:

  getCapabilities in interface CapabilitiesHandler

  Specified by:

  getCapabilities in interface Clusterer

  Returns:

  the capabilities of this object

  See Also:

  • Capabilities

• getRevision

  public String getRevision()

  Returns the revision string.

  Specified by:

  getRevision in interface RevisionHandler

  Returns:

  the revision