weka.classifiers.functions
Class Winnow

java.lang.Object
  |
  +--weka.classifiers.Classifier
        |
        +--weka.classifiers.functions.Winnow

All Implemented Interfaces:

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

public class Winnow

extends Classifier

implements UpdateableClassifier

Implements Winnow and Balanced Winnow algorithms by N. Littlestone. For more information, see

N. Littlestone (1988). Learning quickly when irrelevant attributes are abound: A new linear threshold algorithm. Machine Learning 2, pp. 285-318.

and N. Littlestone (1989). Mistake bounds and logarithmic linear-threshold learning algorithms. Technical report UCSC-CRL-89-11, University of California, Santa Cruz.

Valid options are:

-L
Use the baLanced variant (default: false)

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

-A double
Promotion coefficient alpha. (default 2.0)

-B double
Demotion coefficient beta. (default 0.5)

-W double
Starting weights of the prediction coeffs. (default 2.0)

-H double
Prediction threshold. (default -1.0 == number of attributes)

-S int
Random seed to shuffle the input. (default 1), -1 == no shuffling

Version:

$Revision: 1.7 $

Author:

J. Lindgren (jtlindgrcs.helsinki.fi)

See Also:

Serialized Form

Constructor Summary

Winnow()

Method Summary

java.lang.String	alphaTipText() Returns the tip text for this property
java.lang.String	balancedTipText() Returns the tip text for this property
java.lang.String	betaTipText() Returns the tip text for this property
void	buildClassifier(Instances insts) Builds the classifier
double	classifyInstance(Instance inst) Outputs the prediction for the given instance.
java.lang.String	defaultWeightTipText() Returns the tip text for this property
double	getAlpha() Get the value of Alpha.
boolean	getBalanced() Get the value of Balanced.
double	getBeta() Get the value of Beta.
double	getDefaultWeight() Get the value of defaultWeight.
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.
double	getThreshold() Get the value of Threshold.
java.lang.String	globalInfo() Returns a string describing classifier
java.util.Enumeration	listOptions() Returns an enumeration describing the available options
static void	main(java.lang.String[] argv) Main method.
java.lang.String	numIterationsTipText() Returns the tip text for this property
java.lang.String	seedTipText() Returns the tip text for this property
void	setAlpha(double a) Set the value of Alpha.
void	setBalanced(boolean b) Set the value of Balanced.
void	setBeta(double b) Set the value of Beta.
void	setDefaultWeight(double w) Set the value of defaultWeight.
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.
void	setThreshold(double t) Set the value of Threshold.
java.lang.String	thresholdTipText() Returns the tip text for this property
java.lang.String	toString() Returns textual description of the classifier.
void	updateClassifier(Instance instance) Updates the classifier with a new learning example

Methods inherited from class weka.classifiers.Classifier

debugTipText, distributionForInstance, forName, getDebug, makeCopies, setDebug

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

Winnow

public Winnow()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing classifier

Returns:

a description suitable for displaying in the explorer/experimenter gui

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class Classifier

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.

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class Classifier

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

Overrides:

getOptions in class Classifier

Returns:

an array of strings suitable for passing to setOptions

buildClassifier

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

Builds the classifier

Specified by:

buildClassifier in class Classifier

Parameters:

insts - set of instances serving as training data

Throws:

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

updateClassifier

public void updateClassifier(Instance instance)
                      throws java.lang.Exception

Updates the classifier with a new learning example

Specified by:

updateClassifier in interface UpdateableClassifier

Parameters:

instance - the instance to included

Throws:

java.lang.Exception - if something goes wrong

classifyInstance

public double classifyInstance(Instance inst)
                        throws java.lang.Exception

Outputs the prediction for the given instance.

Overrides:

classifyInstance in class Classifier

Parameters:

inst - the instance for which prediction is to be computed

Returns:

the prediction

Throws:

java.lang.Exception - if something goes wrong

toString

public java.lang.String toString()

Returns textual description of the classifier.

Overrides:

toString in class java.lang.Object

balancedTipText

public java.lang.String balancedTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getBalanced

public boolean getBalanced()

Get the value of Balanced.

Returns:

Value of Balanced.

setBalanced

public void setBalanced(boolean b)

Set the value of Balanced.

Parameters:

b - Value to assign to Balanced.

alphaTipText

public java.lang.String alphaTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getAlpha

public double getAlpha()

Get the value of Alpha.

Returns:

Value of Alpha.

setAlpha

public void setAlpha(double a)

Set the value of Alpha.

Parameters:

a - Value to assign to Alpha.

betaTipText

public java.lang.String betaTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getBeta

public double getBeta()

Get the value of Beta.

Returns:

Value of Beta.

setBeta

public void setBeta(double b)

Set the value of Beta.

Parameters:

b - Value to assign to Beta.

thresholdTipText

public java.lang.String thresholdTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getThreshold

public double getThreshold()

Get the value of Threshold.

Returns:

Value of Threshold.

setThreshold

public void setThreshold(double t)

Set the value of Threshold.

Parameters:

t - Value to assign to Threshold.

defaultWeightTipText

public java.lang.String defaultWeightTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getDefaultWeight

public double getDefaultWeight()

Get the value of defaultWeight.

Returns:

Value of defaultWeight.

setDefaultWeight

public void setDefaultWeight(double w)

Set the value of defaultWeight.

Parameters:

w - Value to assign to defaultWeight.

numIterationsTipText

public java.lang.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.

seedTipText

public java.lang.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.

main

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

Main method.