weka.classifiers
Class VotedPerceptron

java.lang.Object
  |
  +--weka.classifiers.Classifier
        |
        +--weka.classifiers.DistributionClassifier
              |
              +--weka.classifiers.VotedPerceptron

All Implemented Interfaces:

java.lang.Cloneable, OptionHandler, java.io.Serializable

public class VotedPerceptron

extends DistributionClassifier

implements OptionHandler

Implements 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 and R. E. Schapire (1998). Large margin classification using the perceptron algorithm. Proc. 11th Annu. Conf. on Comput. Learning Theory, pp. 209-217, ACM Press, New York, NY.

Valid options are:

-I num
The number of iterations to be performed. (default 1)

-E num
The exponent for the polynomial kernel. (default 1)

-S num
The seed for the random number generator. (default 1)

-M num
The maximum number of alterations allowed. (default 10000)

Author:

Eibe Frank (eibe@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

VotedPerceptron()

Method Summary

void	buildClassifier(Instances insts) Builds the ensemble of perceptrons.
double[]	distributionForInstance(Instance inst) Outputs the distribution for the given output.
double	getExponent() Get the value of exponent.
int	getMaxK() Get the value of maxK.
int	getNumIterations() Get the value of NumIterations.
java.lang.String[]	getOptions() Gets the current settings of the classifier.
int	getSeed() Get the value of Seed.
java.util.Enumeration	listOptions() Returns an enumeration describing the available options
static void	main(java.lang.String[] argv) Main method.
void	setExponent(double v) Set the value of exponent.
void	setMaxK(int v) Set the value of maxK.
void	setNumIterations(int v) Set the value of NumIterations.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setSeed(int v) Set the value of Seed.
java.lang.String	toString() Returns textual description of classifier.

Methods inherited from class weka.classifiers.DistributionClassifier

classifyInstance

Methods inherited from class weka.classifiers.Classifier

forName, makeCopies

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

VotedPerceptron

public VotedPerceptron()

Method Detail

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options

Specified by:

listOptions in interface OptionHandler

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:

-I num
The number of iterations to be performed. (default 1)

-E num
The exponent for the polynomial kernel. (default 1)

-S num
The seed for the random number generator. (default 1)

-M num
The maximum number of alterations allowed. (default 10000)

Specified by:

setOptions in interface OptionHandler

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 in interface OptionHandler

Returns:

an array of strings suitable for passing to setOptions

buildClassifier

public void buildClassifier(Instances insts)
                     throws java.lang.Exception

Builds the ensemble of perceptrons.

Overrides:

buildClassifier in class Classifier

Throws:

java.lang.Exception - if something goes wrong during building

distributionForInstance

public double[] distributionForInstance(Instance inst)
                                 throws java.lang.Exception

Outputs the distribution for the given output. Pipes output of SVM through sigmoid function.

Overrides:

distributionForInstance in class DistributionClassifier

Parameters:

inst - the instance for which distribution is to be computed

Returns:

the distribution

Throws:

java.lang.Exception - if something goes wrong

toString

public java.lang.String toString()

Returns textual description of classifier.

Overrides:

toString in class java.lang.Object

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.

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.

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.

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.

main

public static void main(java.lang.String[] argv)

Main method.