Package weka.classifiers.functions

Class VotedPerceptron

java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.functions.VotedPerceptron
All Implemented Interfaces:
Serializable, Cloneable, Classifier, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, RevisionHandler, TechnicalInformationHandler
public class VotedPerceptron extends AbstractClassifier implements OptionHandler, TechnicalInformationHandler
Implementation of the voted perceptron algorithm by Freund and Schapire. Globally replaces all missing values, and transforms nominal attributes into binary ones.

For more information, see:

Y. Freund, R. E. Schapire: Large margin classification using the perceptron algorithm. In: 11th Annual Conference on Computational Learning Theory, New York, NY, 209-217, 1998.

BibTeX: 

 @inproceedings{Freund1998,
    address = {New York, NY},
    author = {Y. Freund and R. E. Schapire},
    booktitle = {11th Annual Conference on Computational Learning Theory},
    pages = {209-217},
    publisher = {ACM Press},
    title = {Large margin classification using the perceptron algorithm},
    year = {1998}
 }

Valid options are: 

 -I <int>
  The number of iterations to be performed.
  (default 1)
 -E <double>
  The exponent for the polynomial kernel.
  (default 1)
 -S <int>
  The seed for the random number generation.
  (default 1)
 -M <int>
  The maximum number of alterations allowed.
  (default 10000)
Version:
$Revision: 15519 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:

  • Constructor Details

    • VotedPerceptron

      public VotedPerceptron()

  • Method Details

    • globalInfo

      public String globalInfo()
      Returns a string describing this classifier
      Returns:
      a description of the classifier 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

    • listOptions

      public Enumeration<Option> listOptions()
      Returns an enumeration describing the available options.
      Specified by:
      listOptions in interface OptionHandler
      Overrides:
      listOptions in class AbstractClassifier
      Returns:
      an enumeration of all the available options.

    • setOptions

      public void setOptions(String[] options) throws Exception
      Parses a given list of options.

      Valid options are: 

       -I <int>
  The number of iterations to be performed.
  (default 1)
       -E <double>
  The exponent for the polynomial kernel.
  (default 1)
       -S <int>
  The seed for the random number generation.
  (default 1)
       -M <int>
  The maximum number of alterations allowed.
  (default 10000)
      Specified by:
      setOptions in interface OptionHandler
      Overrides:
      setOptions in class AbstractClassifier
      Parameters:
      options - the list of options as an array of strings
      Throws:
      Exception - if an option is not supported

    • getOptions

      public String[] getOptions()
      Gets the current settings of the classifier.
      Specified by:
      getOptions in interface OptionHandler
      Overrides:
      getOptions in class AbstractClassifier
      Returns:
      an array of strings suitable for passing to setOptions

    • getCapabilities

      public Capabilities getCapabilities()
      Returns default capabilities of the classifier.
      Specified by:
      getCapabilities in interface CapabilitiesHandler
      Specified by:
      getCapabilities in interface Classifier
      Overrides:
      getCapabilities in class AbstractClassifier
      Returns:
      the capabilities of this classifier
      See Also:

    • buildClassifier

      public void buildClassifier(Instances insts) throws Exception
      Builds the ensemble of perceptrons.
      Specified by:
      buildClassifier in interface Classifier
      Parameters:
      insts - the data to train the classifier with
      Throws:
      Exception - if something goes wrong during building

    • distributionForInstance

      public double[] distributionForInstance(Instance inst) throws Exception
      Outputs the distribution for the given output. Pipes output of SVM through sigmoid function.
      Specified by:
      distributionForInstance in interface Classifier
      Overrides:
      distributionForInstance in class AbstractClassifier
      Parameters:
      inst - the instance for which distribution is to be computed
      Returns:
      the distribution
      Throws:
      Exception - if something goes wrong

    • toString

      public String toString()
      Returns textual description of classifier.
      Overrides:
      toString in class Object
      Returns:
      the model as string

    • maxKTipText

      public String maxKTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui

    • getMaxK

      public int getMaxK()
      Get the value of maxK.
      Returns:
      Value of maxK.

    • setMaxK

      public void setMaxK(int v)
      Set the value of maxK.
      Parameters:
      v - Value to assign to maxK.

    • numIterationsTipText

      public String numIterationsTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui

    • getNumIterations

      public int getNumIterations()
      Get the value of NumIterations.
      Returns:
      Value of NumIterations.

    • setNumIterations

      public void setNumIterations(int v)
      Set the value of NumIterations.
      Parameters:
      v - Value to assign to NumIterations.

    • exponentTipText

      public String exponentTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui

    • getExponent

      public double getExponent()
      Get the value of exponent.
      Returns:
      Value of exponent.

    • setExponent

      public void setExponent(double v)
      Set the value of exponent.
      Parameters:
      v - Value to assign to exponent.

    • seedTipText

      public String seedTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui

    • getSeed

      public int getSeed()
      Get the value of Seed.
      Returns:
      Value of Seed.

    • setSeed

      public void setSeed(int v)
      Set the value of Seed.
      Parameters:
      v - Value to assign to Seed.

    • getRevision

      public String getRevision()
      Returns the revision string.
      Specified by:
      getRevision in interface RevisionHandler
      Overrides:
      getRevision in class AbstractClassifier
      Returns:
      the revision

    • main

      public static void main(String[] argv)
      Main method.
      Parameters:
      argv - the commandline options