VotedPerceptron (weka-dev 3.7.10 API)

java.lang.Object
- weka.classifiers.AbstractClassifier
- - weka.classifiers.functions.VotedPerceptron

All Implemented Interfaces:: Serializable, Cloneable, Classifier, CapabilitiesHandler, 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: 8034 $
Author:: Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:: Serialized Form

Constructor Summary

Constructors
Constructor and Description

VotedPerceptron()

Constructors
Constructor and Description
`VotedPerceptron()`

Method Summary

Methods
Modifier and Type	Method and Description
`void`	`buildClassifier(Instances insts)` Builds the ensemble of perceptrons.
`double[]`	`distributionForInstance(Instance inst)` Outputs the distribution for the given output.
`String`	`exponentTipText()` Returns the tip text for this property
`Capabilities`	`getCapabilities()` Returns default capabilities of the classifier.
`double`	`getExponent()` Get the value of exponent.
`int`	`getMaxK()` Get the value of maxK.
`int`	`getNumIterations()` Get the value of NumIterations.
`String[]`	`getOptions()` Gets the current settings of the classifier.
`String`	`getRevision()` Returns the revision string.
`int`	`getSeed()` Get the value of Seed.
`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.
`String`	`globalInfo()` Returns a string describing this classifier
`Enumeration`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(String[] argv)` Main method.
`String`	`maxKTipText()` Returns the tip text for this property
`String`	`numIterationsTipText()` Returns the tip text for this property
`String`	`seedTipText()` Returns the tip text for this property
`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(String[] options)` Parses a given list of options.
`void`	`setSeed(int v)` Set the value of Seed.
`String`	`toString()` Returns textual description of classifier.

Methods inherited from class weka.classifiers.AbstractClassifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, runClassifier, setDebug

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - VotedPerceptron
```
public VotedPerceptron()
```
- Method Detail
  - 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 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 Classifier
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class AbstractClassifier
    
    Returns:
    the capabilities of this classifier
    See Also:
    Capabilities
  - 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

Class VotedPerceptron

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.AbstractClassifier

Methods inherited from class java.lang.Object

Constructor Detail

VotedPerceptron

Method Detail

globalInfo

getTechnicalInformation

listOptions

setOptions

getOptions

getCapabilities

buildClassifier

distributionForInstance

toString

maxKTipText

getMaxK

setMaxK

numIterationsTipText

getNumIterations

setNumIterations

exponentTipText

getExponent

setExponent

seedTipText

getSeed

setSeed

getRevision

main