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Class weka.classifiers.meta.RacedIncrementalLogitBoost 

java.lang.Object
    |
    +----weka.classifiers.Classifier
            |
            +----weka.classifiers.DistributionClassifier
                    |
                    +----weka.classifiers.meta.RacedIncrementalLogitBoost
public class RacedIncrementalLogitBoost
extends DistributionClassifier
implements OptionHandler, UpdateableClassifier
Classifier for incremental learning of large datasets by way of racing logit-boosted committees. Valid options are:

-C num
Set the minimum chunk size (default 500).

-M num
Set the maximum chunk size (default 8000).

-V num
Set the validation set size (default 5000).

-D
Turn on debugging output.

-W classname
Specify the full class name of a weak learner as the basis for boosting (required).

-Q
Use resampling instead of reweighting.

-S seed
Random number seed for resampling (default 1).

-P type
The type of pruning to use.

Options after -- are passed to the designated learner.

Version:
$Revision: 1.2 $
Author:
Richard Kirkby (rkirkby@cs.waikato.ac.nz)
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)

Variable Index

o PRUNETYPE_LOGLIKELIHOOD
 
o PRUNETYPE_NONE
The pruning types
o TAGS_PRUNETYPE
 

Constructor Index

o RacedIncrementalLogitBoost()
 

Method Index

o buildClassifier(Instances)
Builds the classifier.
o classifierTipText()
 
o debugTipText()
 
o distributionForInstance(Instance)
Computes class distribution of an instance using the best committee.
o getBestCommitteeChunkSize()
Get the best committee chunk size
o getBestCommitteeErrorEstimate()
Get the best committee's error on the validation data
o getBestCommitteeLLEstimate()
Get the best committee's log likelihood on the validation data
o getBestCommitteeSize()
Get the number of members in the best committee
o getClassifier()
Get the classifier used as the classifier
o getDebug()
Get whether debugging is turned on
o getMaxChunkSize()
Get the maximum chunk size
o getMinChunkSize()
Get the minimum chunk size
o getOptions()
Gets the current settings of the Classifier.
o getPruningType()
Get the pruning type
o getSeed()
Get seed for resampling.
o getUseResampling()
Get whether resampling is turned on
o getValidationChunkSize()
Get the validation chunk size
o globalInfo()
 
o listOptions()
Returns an enumeration describing the available options
o main(String[])
Main method for this class.
o maxChunkSizeTipText()
 
o minChunkSizeTipText()
 
o pruningTypeTipText()
 
o seedTipText()
 
o setClassifier(Classifier)
Set the classifier for boosting.
o setDebug(boolean)
Set debugging mode
o setMaxChunkSize(int)
Set the maximum chunk size
o setMinChunkSize(int)
Set the minimum chunk size
o setOptions(String[])
Parses a given list of options.
o setPruningType(SelectedTag)
Set the pruning type
o setSeed(int)
Set seed for resampling.
o setUseResampling(boolean)
Set resampling mode
o setValidationChunkSize(int)
Set the validation chunk size
o toString()
Returns description of the boosted classifier.
o updateClassifier(Instance)
Updates the classifier.
o useResamplingTipText()
 
o validationChunkSizeTipText()
 

Field Detail

o PRUNETYPE_NONE
public static final int PRUNETYPE_NONE
          The pruning types
o PRUNETYPE_LOGLIKELIHOOD
public static final int PRUNETYPE_LOGLIKELIHOOD
o TAGS_PRUNETYPE
public static final Tag[] TAGS_PRUNETYPE

Constructor Detail

o RacedIncrementalLogitBoost
public RacedIncrementalLogitBoost()

Method Detail

o buildClassifier
public void buildClassifier(Instances data) throws java.lang.Exception
          Builds the classifier.
Parameters:
instances - the instances to train the classifier with
Throws:
java.lang.Exception - if something goes wrong
Overrides:
buildClassifier in class Classifier
o updateClassifier
public void updateClassifier(Instance instance) throws java.lang.Exception
          Updates the classifier.
Parameters:
instance - the next instance in the stream of training data
Throws:
java.lang.Exception - if something goes wrong
o distributionForInstance
public double[] distributionForInstance(Instance instance) throws java.lang.Exception
          Computes class distribution of an instance using the best committee.
Overrides:
distributionForInstance in class DistributionClassifier
o listOptions
public java.util.Enumeration listOptions()
          Returns an enumeration describing the available options
Returns:
an enumeration of all the available options
o setOptions
public void setOptions(java.lang.String options[]) throws java.lang.Exception
          Parses a given list of options. Valid options are:

Parameters:
options - the list of options as an array of strings
Throws:
java.lang.Exception - if an option is not supported
o getOptions
public java.lang.String[] getOptions()
          Gets the current settings of the Classifier.
Returns:
an array of strings suitable for passing to setOptions
o globalInfo
public java.lang.String globalInfo()
Returns:
a description of the classifier suitable for displaying in the explorer/experimenter gui
o classifierTipText
public java.lang.String classifierTipText()
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
o setClassifier
public void setClassifier(Classifier newClassifier)
          Set the classifier for boosting. The learner should be able to handle numeric class attributes.
Parameters:
newClassifier - the Classifier to use.
o getClassifier
public Classifier getClassifier()
          Get the classifier used as the classifier
Returns:
the classifier used as the classifier
o minChunkSizeTipText
public java.lang.String minChunkSizeTipText()
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
o setMinChunkSize
public void setMinChunkSize(int chunkSize)
          Set the minimum chunk size
Parameters:
chunkSize -
o getMinChunkSize
public int getMinChunkSize()
          Get the minimum chunk size
Returns:
the chunk size
o maxChunkSizeTipText
public java.lang.String maxChunkSizeTipText()
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
o setMaxChunkSize
public void setMaxChunkSize(int chunkSize)
          Set the maximum chunk size
Parameters:
chunkSize -
o getMaxChunkSize
public int getMaxChunkSize()
          Get the maximum chunk size
Returns:
the chunk size
o validationChunkSizeTipText
public java.lang.String validationChunkSizeTipText()
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
o setValidationChunkSize
public void setValidationChunkSize(int chunkSize)
          Set the validation chunk size
Parameters:
chunkSize -
o getValidationChunkSize
public int getValidationChunkSize()
          Get the validation chunk size
Returns:
the chunk size
o pruningTypeTipText
public java.lang.String pruningTypeTipText()
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
o setPruningType
public void setPruningType(SelectedTag pruneType)
          Set the pruning type
Parameters:
pruneType -
o getPruningType
public SelectedTag getPruningType()
          Get the pruning type
Returns:
the type
o debugTipText
public java.lang.String debugTipText()
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
o setDebug
public void setDebug(boolean debug)
          Set debugging mode
Parameters:
debug - true if debug output should be printed
o getDebug
public boolean getDebug()
          Get whether debugging is turned on
Returns:
true if debugging output is on
o useResamplingTipText
public java.lang.String useResamplingTipText()
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
o setUseResampling
public void setUseResampling(boolean r)
          Set resampling mode
Parameters:
resampling - true if resampling should be done
o getUseResampling
public boolean getUseResampling()
          Get whether resampling is turned on
Returns:
true if resampling output is on
o seedTipText
public java.lang.String seedTipText()
Returns:
tip text for this property suitable for displaying in the explorer/experimenter gui
o setSeed
public void setSeed(int seed)
          Set seed for resampling.
Parameters:
seed - the seed for resampling
o getSeed
public int getSeed()
          Get seed for resampling.
Returns:
the seed for resampling
o getBestCommitteeChunkSize
public int getBestCommitteeChunkSize()
          Get the best committee chunk size
o getBestCommitteeSize
public int getBestCommitteeSize()
          Get the number of members in the best committee
o getBestCommitteeErrorEstimate
public double getBestCommitteeErrorEstimate()
          Get the best committee's error on the validation data
o getBestCommitteeLLEstimate
public double getBestCommitteeLLEstimate()
          Get the best committee's log likelihood on the validation data
o toString
public java.lang.String toString()
          Returns description of the boosted classifier.
Returns:
description of the boosted classifier as a string
Overrides:
toString in class java.lang.Object
o main
public static void main(java.lang.String argv[])
          Main method for this class.
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