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, RevisionHandler, TechnicalInformationHandler

public class RacedIncrementalLogitBoost
extends RandomizableSingleClassifierEnhancer
implements UpdateableClassifier, TechnicalInformationHandler

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

For more information see:

Eibe Frank, Geoffrey Holmes, Richard Kirkby, Mark Hall: Racing committees for large datasets. In: Proceedings of the 5th International Conferenceon Discovery Science, 153-164, 2002.

BibTeX:

 @inproceedings{Frank2002,
    author = {Eibe Frank and Geoffrey Holmes and Richard Kirkby and Mark Hall},
    booktitle = {Proceedings of the 5th International Conferenceon Discovery Science},
    pages = {153-164},
    publisher = {Springer},
    title = { Racing committees for large datasets},
    year = {2002}
 }

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: 6477 $
Author:: Richard Kirkby (rkirkby@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:: Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`static int`	`PRUNETYPE_LOGLIKELIHOOD` log likelihood pruning
`static int`	`PRUNETYPE_NONE` no pruning
`static Tag[]`	`TAGS_PRUNETYPE` The pruning types

Constructor Summary

Constructors
Constructor and Description

RacedIncrementalLogitBoost()
Constructor.

Constructors
Constructor and Description
`RacedIncrementalLogitBoost()` Constructor.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`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
`java.lang.String`	`getRevision()` Returns the revision string.
`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.
`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
  - 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
  - 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
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class Classifier
    
    Returns:
    
    the revision
  - main
```
public static void main(java.lang.String[] argv)
```
    Main method for this class.
    
    Parameters:
    
    argv - the commandline parameters

Class RacedIncrementalLogitBoost

Field Summary

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.RandomizableSingleClassifierEnhancer

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

Methods inherited from class weka.classifiers.Classifier

Methods inherited from class java.lang.Object

Field Detail

PRUNETYPE_NONE

PRUNETYPE_LOGLIKELIHOOD

TAGS_PRUNETYPE

Constructor Detail

RacedIncrementalLogitBoost

Method Detail

getCapabilities

buildClassifier

updateClassifier

distributionForInstance

listOptions

setOptions

getOptions

globalInfo

getTechnicalInformation

setClassifier

minChunkSizeTipText

setMinChunkSize

getMinChunkSize

maxChunkSizeTipText

setMaxChunkSize

getMaxChunkSize

validationChunkSizeTipText

setValidationChunkSize

getValidationChunkSize

pruningTypeTipText

setPruningType

getPruningType

useResamplingTipText

setUseResampling

getUseResampling

getBestCommitteeChunkSize

getBestCommitteeSize

getBestCommitteeErrorEstimate

getBestCommitteeLLEstimate

toString

getRevision

main