RBFNetwork (original) (raw)

• java.lang.Object

• • weka.classifiers.Classifier
  • • weka.classifiers.functions.RBFNetwork

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

public class RBFNetwork
extends Classifier
implements OptionHandler
Class that implements a normalized Gaussian radial basisbasis function network.
It uses the k-means clustering algorithm to provide the basis functions and learns either a logistic regression (discrete class problems) or linear regression (numeric class problems) on top of that. Symmetric multivariate Gaussians are fit to the data from each cluster. If the class is nominal it uses the given number of clusters per class.It standardizes all numeric attributes to zero mean and unit variance.
Valid options are:
-B
Set the number of clusters (basis functions) to generate. (default = 2).
-S
Set the random seed to be used by K-means. (default = 1).
-R
Set the ridge value for the logistic or linear regression.
-M
Set the maximum number of iterations for the logistic regression. (default -1, until convergence).
-W
Set the minimum standard deviation for the clusters. (default 0.1).
Version: Revision:1.10Revision: 1.10 Revision:1.10
Author:
Mark Hall, Eibe Frank
See Also:
Serialized Form

• • Constructor Summary

  Constructors

  Constructor and Description
  RBFNetwork()

  • Method Summary

  All Methods Static Methods Instance Methods Concrete Methods

  Modifier and Type	Method and Description
  void	buildClassifier(Instances instances) Builds the classifier
  java.lang.String	clusteringSeedTipText() Returns the tip text for this property
  double[]	distributionForInstance(Instance instance) Computes the distribution for a given instance
  Capabilities	getCapabilities() Returns default capabilities of the classifier, i.e., and "or" of Logistic and LinearRegression.
  int	getClusteringSeed() Get the random seed used by K-means.
  int	getMaxIts() Get the value of MaxIts.
  double	getMinStdDev() Get the MinStdDev value.
  int	getNumClusters() Return the number of clusters to generate.
  java.lang.String[]	getOptions() Gets the current settings of the classifier.
  java.lang.String	getRevision() Returns the revision string.
  double	getRidge() Gets the ridge value.
  java.lang.String	globalInfo() Returns a string describing this classifier
  java.util.Enumeration	listOptions() Returns an enumeration describing the available options
  static void	main(java.lang.String[] argv) Main method for testing this class.
  java.lang.String	maxItsTipText() Returns the tip text for this property
  java.lang.String	minStdDevTipText() Returns the tip text for this property
  java.lang.String	numClustersTipText() Returns the tip text for this property
  java.lang.String	ridgeTipText() Returns the tip text for this property
  void	setClusteringSeed(int seed) Set the random seed to be passed on to K-means.
  void	setMaxIts(int newMaxIts) Set the value of MaxIts.
  void	setMinStdDev(double newMinStdDev) Set the MinStdDev value.
  void	setNumClusters(int numClusters) Set the number of clusters for K-means to generate.
  void	setOptions(java.lang.String[] options) Parses a given list of options.
  void	setRidge(double ridge) Sets the ridge value for logistic or linear regression.
  java.lang.String	toString() Returns a description of this classifier as a String

     * ### Methods inherited from class weka.classifiers.[Classifier](../../../weka/classifiers/Classifier.html "class in weka.classifiers")  
     `[classifyInstance](../../../weka/classifiers/Classifier.html#classifyInstance-weka.core.Instance-), [debugTipText](../../../weka/classifiers/Classifier.html#debugTipText--), [forName](../../../weka/classifiers/Classifier.html#forName-java.lang.String-java.lang.String:A-), [getDebug](../../../weka/classifiers/Classifier.html#getDebug--), [makeCopies](../../../weka/classifiers/Classifier.html#makeCopies-weka.classifiers.Classifier-int-), [makeCopy](../../../weka/classifiers/Classifier.html#makeCopy-weka.classifiers.Classifier-), [setDebug](../../../weka/classifiers/Classifier.html#setDebug-boolean-)`  
     * ### Methods inherited from class java.lang.Object  
     `equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`

• • Constructor Detail

     * #### RBFNetwork  
     public RBFNetwork()  

  • Method Detail

    * #### globalInfo  
    public java.lang.String globalInfo()  
    Returns a string describing this classifier  
    Returns:  
    a description of the classifier suitable for displaying in the explorer/experimenter gui  
    * #### getCapabilities  
    public [Capabilities](../../../weka/core/Capabilities.html "class in weka.core") getCapabilities()  
    Returns default capabilities of the classifier, i.e., and "or" of Logistic and LinearRegression.  
    Specified by:  
    `[getCapabilities](../../../weka/core/CapabilitiesHandler.html#getCapabilities--)` in interface `[CapabilitiesHandler](../../../weka/core/CapabilitiesHandler.html "interface in weka.core")`  
    Overrides:  
    `[getCapabilities](../../../weka/classifiers/Classifier.html#getCapabilities--)` in class `[Classifier](../../../weka/classifiers/Classifier.html "class in weka.classifiers")`  
    Returns:  
    the capabilities of this classifier  
    See Also:  
    [Logistic](../../../weka/classifiers/functions/Logistic.html "class in weka.classifiers.functions"), [LinearRegression](../../../weka/classifiers/functions/LinearRegression.html "class in weka.classifiers.functions")  
    * #### buildClassifier  
    public void buildClassifier([Instances](../../../weka/core/Instances.html "class in weka.core") instances)  
                         throws java.lang.Exception  
    Builds the classifier  
    Specified by:  
    `[buildClassifier](../../../weka/classifiers/Classifier.html#buildClassifier-weka.core.Instances-)` in class `[Classifier](../../../weka/classifiers/Classifier.html "class in weka.classifiers")`  
    Parameters:  
    `instances` \- the training data  
    Throws:  
    `java.lang.Exception` \- if the classifier could not be built successfully  
    * #### distributionForInstance  
    public double[] distributionForInstance([Instance](../../../weka/core/Instance.html "class in weka.core") instance)  
                                     throws java.lang.Exception  
    Computes the distribution for a given instance  
    Overrides:  
    `[distributionForInstance](../../../weka/classifiers/Classifier.html#distributionForInstance-weka.core.Instance-)` in class `[Classifier](../../../weka/classifiers/Classifier.html "class in weka.classifiers")`  
    Parameters:  
    `instance` \- the instance for which distribution is computed  
    Returns:  
    the distribution  
    Throws:  
    `java.lang.Exception` \- if the distribution can't be computed successfully  
    * #### toString  
    public java.lang.String toString()  
    Returns a description of this classifier as a String  
    Overrides:  
    `toString` in class `java.lang.Object`  
    Returns:  
    a description of this classifier  
    * #### maxItsTipText  
    public java.lang.String maxItsTipText()  
    Returns the tip text for this property  
    Returns:  
    tip text for this property suitable for displaying in the explorer/experimenter gui  
    * #### getMaxIts  
    public int getMaxIts()  
    Get the value of MaxIts.  
    Returns:  
    Value of MaxIts.  
    * #### setMaxIts  
    public void setMaxIts(int newMaxIts)  
    Set the value of MaxIts.  
    Parameters:  
    `newMaxIts` \- Value to assign to MaxIts.  
    * #### ridgeTipText  
    public java.lang.String ridgeTipText()  
    Returns the tip text for this property  
    Returns:  
    tip text for this property suitable for displaying in the explorer/experimenter gui  
    * #### setRidge  
    public void setRidge(double ridge)  
    Sets the ridge value for logistic or linear regression.  
    Parameters:  
    `ridge` \- the ridge  
    * #### getRidge  
    public double getRidge()  
    Gets the ridge value.  
    Returns:  
    the ridge  
    * #### 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 numClusters)  
    Set the number of clusters for K-means to generate.  
    Parameters:  
    `numClusters` \- the number of clusters to generate.  
    * #### getNumClusters  
    public int getNumClusters()  
    Return the number of clusters to generate.  
    Returns:  
    the number of clusters to generate.  
    * #### clusteringSeedTipText  
    public java.lang.String clusteringSeedTipText()  
    Returns the tip text for this property  
    Returns:  
    tip text for this property suitable for displaying in the explorer/experimenter gui  
    * #### setClusteringSeed  
    public void setClusteringSeed(int seed)  
    Set the random seed to be passed on to K-means.  
    Parameters:  
    `seed` \- a seed value.  
    * #### getClusteringSeed  
    public int getClusteringSeed()  
    Get the random seed used by K-means.  
    Returns:  
    the seed value.  
    * #### minStdDevTipText  
    public java.lang.String minStdDevTipText()  
    Returns the tip text for this property  
    Returns:  
    tip text for this property suitable for displaying in the explorer/experimenter gui  
    * #### getMinStdDev  
    public double getMinStdDev()  
    Get the MinStdDev value.  
    Returns:  
    the MinStdDev value.  
    * #### setMinStdDev  
    public void setMinStdDev(double newMinStdDev)  
    Set the MinStdDev value.  
    Parameters:  
    `newMinStdDev` \- The new MinStdDev value.  
    * #### listOptions  
    public java.util.Enumeration listOptions()  
    Returns an enumeration describing the available options  
    Specified by:  
    `[listOptions](../../../weka/core/OptionHandler.html#listOptions--)` in interface `[OptionHandler](../../../weka/core/OptionHandler.html "interface in weka.core")`  
    Overrides:  
    `[listOptions](../../../weka/classifiers/Classifier.html#listOptions--)` in class `[Classifier](../../../weka/classifiers/Classifier.html "class in weka.classifiers")`  
    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:  
     -B <number>  
      Set the number of clusters (basis functions) to generate. (default = 2).  
     -S <seed>  
      Set the random seed to be used by K-means. (default = 1).  
     -R <ridge>  
      Set the ridge value for the logistic or linear regression.  
     -M <number>  
      Set the maximum number of iterations for the logistic regression. (default -1, until convergence).  
     -W <number>  
      Set the minimum standard deviation for the clusters. (default 0.1).  
    Specified by:  
    `[setOptions](../../../weka/core/OptionHandler.html#setOptions-java.lang.String:A-)` in interface `[OptionHandler](../../../weka/core/OptionHandler.html "interface in weka.core")`  
    Overrides:  
    `[setOptions](../../../weka/classifiers/Classifier.html#setOptions-java.lang.String:A-)` in class `[Classifier](../../../weka/classifiers/Classifier.html "class in weka.classifiers")`  
    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 classifier.  
    Specified by:  
    `[getOptions](../../../weka/core/OptionHandler.html#getOptions--)` in interface `[OptionHandler](../../../weka/core/OptionHandler.html "interface in weka.core")`  
    Overrides:  
    `[getOptions](../../../weka/classifiers/Classifier.html#getOptions--)` in class `[Classifier](../../../weka/classifiers/Classifier.html "class in weka.classifiers")`  
    Returns:  
    an array of strings suitable for passing to setOptions  
    * #### getRevision  
    public java.lang.String getRevision()  
    Returns the revision string.  
    Specified by:  
    `[getRevision](../../../weka/core/RevisionHandler.html#getRevision--)` in interface `[RevisionHandler](../../../weka/core/RevisionHandler.html "interface in weka.core")`  
    Overrides:  
    `[getRevision](../../../weka/classifiers/Classifier.html#getRevision--)` in class `[Classifier](../../../weka/classifiers/Classifier.html "class in weka.classifiers")`  
    Returns:  
    the revision  
    * #### main  
    public static void main(java.lang.String[] argv)  
    Main method for testing this class.  
    Parameters:  
    `argv` \- should contain the command line arguments to the scheme (see Evaluation)