weka.classifiers.meta
Class RacedIncrementalLogitBoost

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.SingleClassifierEnhancer
          weka.classifiers.RandomizableSingleClassifierEnhancer
              weka.classifiers.meta.RacedIncrementalLogitBoost

All Implemented Interfaces:

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

public class RacedIncrementalLogitBoost
extends RandomizableSingleClassifierEnhancer
implements UpdateableClassifier

Classifier for incremental learning of large datasets by way of racing logit-boosted committees.

Valid options are:

 -C <num>
  Minimum size of chunks.
  (default 500)

 -M <num>
  Maximum size of chunks.
  (default 2000)

 -V <num>
  Size of validation set.
  (default 1000)

 -P <pruning type>
  Committee pruning to perform.
  0=none, 1=log likelihood (default)

 -Q
  Use resampling for boosting.

 -S <num>
  Random number seed.
  (default 1)

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

 -W
  Full name of base classifier.
  (default: weka.classifiers.trees.DecisionStump)

 
 Options specific to classifier weka.classifiers.trees.DecisionStump:
 

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

Options after -- are passed to the designated learner.

Version:

$Revision: 1.11 $

Author:

Richard Kirkby (rkirkby@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)

See Also:

Serialized Form

Field Summary

static int	PRUNETYPE_LOGLIKELIHOOD log likelihood pruning
static int	PRUNETYPE_NONE no pruning
static Tag[]	TAGS_PRUNETYPE The pruning types

Constructor Summary

RacedIncrementalLogitBoost()
Constructor.

Method Summary

void	buildClassifier(Instances data) Builds the classifier.
double[]	distributionForInstance(Instance instance) Computes class distribution of an instance using the best committee.
int	getBestCommitteeChunkSize() Get the best committee chunk size
double	getBestCommitteeErrorEstimate() Get the best committee's error on the validation data
double	getBestCommitteeLLEstimate() Get the best committee's log likelihood on the validation data
int	getBestCommitteeSize() Get the number of members in the best committee
Capabilities	getCapabilities() Returns default capabilities of the classifier.
int	getMaxChunkSize() Get the maximum chunk size
int	getMinChunkSize() Get the minimum chunk size
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
SelectedTag	getPruningType() Get the pruning type
boolean	getUseResampling() Get whether resampling is turned on
int	getValidationChunkSize() Get the validation chunk size
java.lang.String	globalInfo()
java.util.Enumeration	listOptions() Returns an enumeration describing the available options
static void	main(java.lang.String[] argv) Main method for this class.
java.lang.String	maxChunkSizeTipText()
java.lang.String	minChunkSizeTipText()
java.lang.String	pruningTypeTipText()
void	setClassifier(Classifier newClassifier) Set the base learner.
void	setMaxChunkSize(int chunkSize) Set the maximum chunk size
void	setMinChunkSize(int chunkSize) Set the minimum chunk size
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setPruningType(SelectedTag pruneType) Set the pruning type
void	setUseResampling(boolean r) Set resampling mode
void	setValidationChunkSize(int chunkSize) Set the validation chunk size
java.lang.String	toString() Returns description of the boosted classifier.
void	updateClassifier(Instance instance) Updates the classifier.
java.lang.String	useResamplingTipText()
java.lang.String	validationChunkSizeTipText()

Methods inherited from class weka.classifiers.RandomizableSingleClassifierEnhancer

getSeed, seedTipText, setSeed

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, getClassifier

Methods inherited from class weka.classifiers.Classifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug

Methods inherited from class java.lang.Object

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

Field Detail

PRUNETYPE_NONE

public static final int PRUNETYPE_NONE

no pruning

See Also:

Constant Field Values

PRUNETYPE_LOGLIKELIHOOD

public static final int PRUNETYPE_LOGLIKELIHOOD

log likelihood pruning

See Also:

Constant Field Values

TAGS_PRUNETYPE

public static final Tag[] TAGS_PRUNETYPE

The pruning types

Constructor Detail

RacedIncrementalLogitBoost

public RacedIncrementalLogitBoost()

Constructor.

Method Detail

getCapabilities

public Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class SingleClassifierEnhancer

Returns:

the capabilities of this classifier

See Also:

Capabilities

buildClassifier

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

Builds the classifier.

Specified by:

buildClassifier in class Classifier

Parameters:

data - the instances to train the classifier with

Throws:

java.lang.Exception - if something goes wrong

updateClassifier

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

Updates the classifier.

Specified by:

updateClassifier in interface UpdateableClassifier

Parameters:

instance - the next instance in the stream of training data

Throws:

java.lang.Exception - if something goes wrong

distributionForInstance

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

Computes class distribution of an instance using the best committee.

Overrides:

distributionForInstance in class Classifier

Parameters:

instance - the instance to get the distribution for

Returns:

the distribution

Throws:

java.lang.Exception - if anything goes wrong

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class RandomizableSingleClassifierEnhancer

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:

 -C <num>
  Minimum size of chunks.
  (default 500)

 -M <num>
  Maximum size of chunks.
  (default 2000)

 -V <num>
  Size of validation set.
  (default 1000)

 -P <pruning type>
  Committee pruning to perform.
  0=none, 1=log likelihood (default)

 -Q
  Use resampling for boosting.

 -S <num>
  Random number seed.
  (default 1)

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

 -W
  Full name of base classifier.
  (default: weka.classifiers.trees.DecisionStump)

 
 Options specific to classifier weka.classifiers.trees.DecisionStump:
 

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class RandomizableSingleClassifierEnhancer

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 RandomizableSingleClassifierEnhancer

Returns:

an array of strings suitable for passing to setOptions

globalInfo

public java.lang.String globalInfo()

Returns:

a description of the classifier suitable for displaying in the explorer/experimenter gui

setClassifier

public void setClassifier(Classifier newClassifier)

Set the base learner.

Overrides:

setClassifier in class SingleClassifierEnhancer

Parameters:

newClassifier - the classifier to use.

Throws:

java.lang.IllegalArgumentException - if base classifier cannot handle numeric class

minChunkSizeTipText

public java.lang.String minChunkSizeTipText()

Returns:

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

setMinChunkSize

public void setMinChunkSize(int chunkSize)

Set the minimum chunk size

Parameters:

chunkSize - the minimum chunk size

getMinChunkSize

public int getMinChunkSize()

Get the minimum chunk size

Returns:

the chunk size

maxChunkSizeTipText

public java.lang.String maxChunkSizeTipText()

Returns:

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

setMaxChunkSize

public void setMaxChunkSize(int chunkSize)

Set the maximum chunk size

Parameters:

chunkSize - the maximum chunk size

getMaxChunkSize

public int getMaxChunkSize()

Get the maximum chunk size

Returns:

the chunk size

validationChunkSizeTipText

public java.lang.String validationChunkSizeTipText()

Returns:

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

setValidationChunkSize

public void setValidationChunkSize(int chunkSize)

Set the validation chunk size

Parameters:

chunkSize - the validation chunk size

getValidationChunkSize

public int getValidationChunkSize()

Get the validation chunk size

Returns:

the chunk size

pruningTypeTipText

public java.lang.String pruningTypeTipText()

Returns:

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

setPruningType

public void setPruningType(SelectedTag pruneType)

Set the pruning type

Parameters:

pruneType - the pruning type

getPruningType

public SelectedTag getPruningType()

Get the pruning type

Returns:

the type

useResamplingTipText

public java.lang.String useResamplingTipText()

Returns:

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

setUseResampling

public void setUseResampling(boolean r)

Set resampling mode

Parameters:

r - true if resampling should be done

getUseResampling

public boolean getUseResampling()

Get whether resampling is turned on

Returns:

true if resampling output is on

getBestCommitteeChunkSize

public int getBestCommitteeChunkSize()

Get the best committee chunk size

Returns:

the best committee chunk size

getBestCommitteeSize

public int getBestCommitteeSize()

Get the number of members in the best committee

Returns:

the number of members

getBestCommitteeErrorEstimate

public double getBestCommitteeErrorEstimate()

Get the best committee's error on the validation data

Returns:

the best committee's error

getBestCommitteeLLEstimate

public double getBestCommitteeLLEstimate()

Get the best committee's log likelihood on the validation data

Returns:

best committee's log likelihood

toString

public java.lang.String toString()

Returns description of the boosted classifier.

Overrides:

toString in class java.lang.Object

Returns:

description of the boosted classifier as a string

main

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

Main method for this class.

Parameters:

argv - the commandline parameters