类 RBFNetwork

java.lang.Object
weka.classifiers.Classifier
weka.classifiers.functions.RBFNetwork
所有已实现的接口:
Serializable, 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 <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).
版本:
$Revision: 1.10 $
作者:
Mark Hall, Eibe Frank
另请参阅:
  • 构造器详细资料

    • RBFNetwork

      public RBFNetwork()
  • 方法详细资料

    • globalInfo

      public String globalInfo()
      Returns a string describing this classifier
      返回:
      a description of the classifier suitable for displaying in the explorer/experimenter gui
    • getCapabilities

      public Capabilities getCapabilities()
      Returns default capabilities of the classifier, i.e., and "or" of Logistic and LinearRegression.
      指定者:
      getCapabilities 在接口中 CapabilitiesHandler
      覆盖:
      getCapabilities 在类中 Classifier
      返回:
      the capabilities of this classifier
      另请参阅:
    • buildClassifier

      public void buildClassifier(Instances instances) throws Exception
      Builds the classifier
      指定者:
      buildClassifier 在类中 Classifier
      参数:
      instances - the training data
      抛出:
      Exception - if the classifier could not be built successfully
    • distributionForInstance

      public double[] distributionForInstance(Instance instance) throws Exception
      Computes the distribution for a given instance
      覆盖:
      distributionForInstance 在类中 Classifier
      参数:
      instance - the instance for which distribution is computed
      返回:
      the distribution
      抛出:
      Exception - if the distribution can't be computed successfully
    • toString

      public String toString()
      Returns a description of this classifier as a String
      覆盖:
      toString 在类中 Object
      返回:
      a description of this classifier
    • maxItsTipText

      public String maxItsTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • getMaxIts

      public int getMaxIts()
      Get the value of MaxIts.
      返回:
      Value of MaxIts.
    • setMaxIts

      public void setMaxIts(int newMaxIts)
      Set the value of MaxIts.
      参数:
      newMaxIts - Value to assign to MaxIts.
    • ridgeTipText

      public String ridgeTipText()
      Returns the tip text for this property
      返回:
      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.
      参数:
      ridge - the ridge
    • getRidge

      public double getRidge()
      Gets the ridge value.
      返回:
      the ridge
    • numClustersTipText

      public String numClustersTipText()
      Returns the tip text for this property
      返回:
      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.
      参数:
      numClusters - the number of clusters to generate.
    • getNumClusters

      public int getNumClusters()
      Return the number of clusters to generate.
      返回:
      the number of clusters to generate.
    • clusteringSeedTipText

      public String clusteringSeedTipText()
      Returns the tip text for this property
      返回:
      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.
      参数:
      seed - a seed value.
    • getClusteringSeed

      public int getClusteringSeed()
      Get the random seed used by K-means.
      返回:
      the seed value.
    • minStdDevTipText

      public String minStdDevTipText()
      Returns the tip text for this property
      返回:
      tip text for this property suitable for displaying in the explorer/experimenter gui
    • getMinStdDev

      public double getMinStdDev()
      Get the MinStdDev value.
      返回:
      the MinStdDev value.
    • setMinStdDev

      public void setMinStdDev(double newMinStdDev)
      Set the MinStdDev value.
      参数:
      newMinStdDev - The new MinStdDev value.
    • listOptions

      public Enumeration listOptions()
      Returns an enumeration describing the available options
      指定者:
      listOptions 在接口中 OptionHandler
      覆盖:
      listOptions 在类中 Classifier
      返回:
      an enumeration of all the available options
    • setOptions

      public void setOptions(String[] options) throws 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).
      指定者:
      setOptions 在接口中 OptionHandler
      覆盖:
      setOptions 在类中 Classifier
      参数:
      options - the list of options as an array of strings
      抛出:
      Exception - if an option is not supported
    • getOptions

      public String[] getOptions()
      Gets the current settings of the classifier.
      指定者:
      getOptions 在接口中 OptionHandler
      覆盖:
      getOptions 在类中 Classifier
      返回:
      an array of strings suitable for passing to setOptions
    • getRevision

      public String getRevision()
      Returns the revision string.
      指定者:
      getRevision 在接口中 RevisionHandler
      覆盖:
      getRevision 在类中 Classifier
      返回:
      the revision
    • main

      public static void main(String[] argv)
      Main method for testing this class.
      参数:
      argv - should contain the command line arguments to the scheme (see Evaluation)