Package weka.classifiers.meta
Class RacedIncrementalLogitBoost
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.RandomizableSingleClassifierEnhancer
weka.classifiers.meta.RacedIncrementalLogitBoost
- All Implemented Interfaces:
Serializable
,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:
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 consoleOptions 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:
-
Field Summary
FieldsModifier and TypeFieldDescriptionstatic final int
log likelihood pruningstatic final int
no pruningstatic final Tag[]
The pruning types -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoid
buildClassifier
(Instances data) Builds the classifier.double[]
distributionForInstance
(Instance instance) Computes class distribution of an instance using the best committee.int
Get the best committee chunk sizedouble
Get the best committee's error on the validation datadouble
Get the best committee's log likelihood on the validation dataint
Get the number of members in the best committeeReturns default capabilities of the classifier.int
Get the maximum chunk sizeint
Get the minimum chunk sizeString[]
Gets the current settings of the Classifier.Get the pruning typeReturns the revision string.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
Get whether resampling is turned onint
Get the validation chunk sizeReturns an enumeration describing the available optionsstatic void
Main method for this class.void
setClassifier
(Classifier newClassifier) Set the base learner.void
setMaxChunkSize
(int chunkSize) Set the maximum chunk sizevoid
setMinChunkSize
(int chunkSize) Set the minimum chunk sizevoid
setOptions
(String[] options) Parses a given list of options.void
setPruningType
(SelectedTag pruneType) Set the pruning typevoid
setUseResampling
(boolean r) Set resampling modevoid
setValidationChunkSize
(int chunkSize) Set the validation chunk sizetoString()
Returns description of the boosted classifier.void
updateClassifier
(Instance instance) Updates the classifier.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
-
Field Details
-
PRUNETYPE_NONE
public static final int PRUNETYPE_NONEno pruning- See Also:
-
PRUNETYPE_LOGLIKELIHOOD
public static final int PRUNETYPE_LOGLIKELIHOODlog likelihood pruning- See Also:
-
TAGS_PRUNETYPE
The pruning types
-
-
Constructor Details
-
RacedIncrementalLogitBoost
public RacedIncrementalLogitBoost()Constructor.
-
-
Method Details
-
getCapabilities
Returns default capabilities of the classifier.- Specified by:
getCapabilities
in interfaceCapabilitiesHandler
- Overrides:
getCapabilities
in classSingleClassifierEnhancer
- Returns:
- the capabilities of this classifier
- See Also:
-
buildClassifier
Builds the classifier.- Specified by:
buildClassifier
in classClassifier
- Parameters:
data
- the instances to train the classifier with- Throws:
Exception
- if something goes wrong
-
updateClassifier
Updates the classifier.- Specified by:
updateClassifier
in interfaceUpdateableClassifier
- Parameters:
instance
- the next instance in the stream of training data- Throws:
Exception
- if something goes wrong
-
distributionForInstance
Computes class distribution of an instance using the best committee.- Overrides:
distributionForInstance
in classClassifier
- Parameters:
instance
- the instance to get the distribution for- Returns:
- the distribution
- Throws:
Exception
- if anything goes wrong
-
listOptions
Returns an enumeration describing the available options- Specified by:
listOptions
in interfaceOptionHandler
- Overrides:
listOptions
in classRandomizableSingleClassifierEnhancer
- Returns:
- an enumeration of all the available options
-
setOptions
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 interfaceOptionHandler
- Overrides:
setOptions
in classRandomizableSingleClassifierEnhancer
- Parameters:
options
- the list of options as an array of strings- Throws:
Exception
- if an option is not supported
-
getOptions
Gets the current settings of the Classifier.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classRandomizableSingleClassifierEnhancer
- Returns:
- an array of strings suitable for passing to setOptions
-
globalInfo
- Returns:
- a description of the classifier suitable for displaying in the explorer/experimenter gui
-
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 interfaceTechnicalInformationHandler
- Returns:
- the technical information about this class
-
setClassifier
Set the base learner.- Overrides:
setClassifier
in classSingleClassifierEnhancer
- Parameters:
newClassifier
- the classifier to use.- Throws:
IllegalArgumentException
- if base classifier cannot handle numeric class
-
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
- 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
- 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
- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
-
setPruningType
Set the pruning type- Parameters:
pruneType
- the pruning type
-
getPruningType
Get the pruning type- Returns:
- the type
-
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
Returns description of the boosted classifier. -
getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classClassifier
- Returns:
- the revision
-
main
Main method for this class.- Parameters:
argv
- the commandline parameters
-