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java.lang.Objectweka.classifiers.Classifier
weka.classifiers.DistributionClassifier
weka.classifiers.meta.RacedIncrementalLogitBoost
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.
Nested Class Summary | |
protected class |
RacedIncrementalLogitBoost.Committee
|
Field Summary | |
protected RacedIncrementalLogitBoost.Committee |
m_bestCommittee
The current best committee |
protected Attribute |
m_ClassAttribute
The actual class attribute (for getting class names) |
protected Classifier |
m_Classifier
The model base classifier to use |
protected FastVector |
m_committees
The committees |
protected Instances |
m_currentSet
The instances currently in memory for training |
protected boolean |
m_Debug
Whether to output debug messages |
protected int |
m_maxBatchSizeRequired
The maximum number of instances required for processing |
protected int |
m_maxChunkSize
The maimum chunk size used for training |
protected int |
m_minChunkSize
The minimum chunk size used for training |
protected int |
m_NumClasses
The number of classes |
protected Instances |
m_NumericClassData
Dummy dataset with a numeric class |
protected int |
m_numInstancesConsumed
The number of instances consumed |
protected int |
m_PruningType
The pruning type used |
protected java.util.Random |
m_RandomInstance
The random number generator used |
protected int |
m_Seed
Seed for boosting with resampling. |
protected boolean |
m_UseResampling
Whether to use resampling |
protected int |
m_validationChunkSize
The size of the validation set |
protected Instances |
m_validationSet
The instances used for validation |
protected boolean |
m_validationSetChanged
Whether the validation set has recently been changed |
protected ZeroR |
m_zeroR
The default scheme used when committees aren't ready |
static int |
PRUNETYPE_LOGLIKELIHOOD
|
static int |
PRUNETYPE_NONE
The pruning types |
static Tag[] |
TAGS_PRUNETYPE
|
protected static double |
Z_MAX
A threshold for responses (Friedman suggests between 2 and 4) |
Constructor Summary | |
RacedIncrementalLogitBoost()
|
Method Summary | |
void |
buildClassifier(Instances data)
Builds the classifier. |
java.lang.String |
classifierTipText()
|
java.lang.String |
debugTipText()
|
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 |
Classifier |
getClassifier()
Get the classifier used as the classifier |
boolean |
getDebug()
Get whether debugging is turned on |
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 |
int |
getSeed()
Get seed for resampling. |
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()
|
protected static double |
RtoP(double[] Fs,
int j)
Convert from function responses to probabilities |
java.lang.String |
seedTipText()
|
void |
setClassifier(Classifier newClassifier)
Set the classifier for boosting. |
void |
setDebug(boolean debug)
Set debugging mode |
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 |
setSeed(int seed)
Set seed for resampling. |
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.DistributionClassifier |
calculateEntropy, calculateLabeledInstanceMargin, calculateMargin, classifyInstance |
Methods inherited from class weka.classifiers.Classifier |
forName, makeCopies |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Field Detail |
public static final int PRUNETYPE_NONE
public static final int PRUNETYPE_LOGLIKELIHOOD
public static final Tag[] TAGS_PRUNETYPE
protected Classifier m_Classifier
protected FastVector m_committees
protected int m_PruningType
protected boolean m_UseResampling
protected int m_Seed
protected int m_NumClasses
protected static final double Z_MAX
protected Instances m_NumericClassData
protected Attribute m_ClassAttribute
protected int m_minChunkSize
protected int m_maxChunkSize
protected int m_validationChunkSize
protected int m_numInstancesConsumed
protected Instances m_validationSet
protected Instances m_currentSet
protected RacedIncrementalLogitBoost.Committee m_bestCommittee
protected ZeroR m_zeroR
protected boolean m_validationSetChanged
protected int m_maxBatchSizeRequired
protected boolean m_Debug
protected java.util.Random m_RandomInstance
Constructor Detail |
public RacedIncrementalLogitBoost()
Method Detail |
public void buildClassifier(Instances data) throws java.lang.Exception
buildClassifier
in class Classifier
data
- set of instances serving as training data
java.lang.Exception
- if something goes wrongpublic void updateClassifier(Instance instance) throws java.lang.Exception
updateClassifier
in interface UpdateableClassifier
instance
- the next instance in the stream of training data
java.lang.Exception
- if something goes wrongprotected static double RtoP(double[] Fs, int j) throws java.lang.Exception
j
- the class value of interest
java.lang.Exception
public double[] distributionForInstance(Instance instance) throws java.lang.Exception
distributionForInstance
in class DistributionClassifier
instance
- the instance to be classified
java.lang.Exception
- if distribution could not be
computed successfullypublic java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
public void setOptions(java.lang.String[] options) throws java.lang.Exception
setOptions
in interface OptionHandler
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
public java.lang.String globalInfo()
public java.lang.String classifierTipText()
public void setClassifier(Classifier newClassifier)
newClassifier
- the Classifier to use.public Classifier getClassifier()
public java.lang.String minChunkSizeTipText()
public void setMinChunkSize(int chunkSize)
chunkSize
- public int getMinChunkSize()
public java.lang.String maxChunkSizeTipText()
public void setMaxChunkSize(int chunkSize)
chunkSize
- public int getMaxChunkSize()
public java.lang.String validationChunkSizeTipText()
public void setValidationChunkSize(int chunkSize)
chunkSize
- public int getValidationChunkSize()
public java.lang.String pruningTypeTipText()
public void setPruningType(SelectedTag pruneType)
pruneType
- public SelectedTag getPruningType()
public java.lang.String debugTipText()
public void setDebug(boolean debug)
debug
- true if debug output should be printedpublic boolean getDebug()
public java.lang.String useResamplingTipText()
public void setUseResampling(boolean r)
public boolean getUseResampling()
public java.lang.String seedTipText()
public void setSeed(int seed)
seed
- the seed for resamplingpublic int getSeed()
public int getBestCommitteeChunkSize()
public int getBestCommitteeSize()
public double getBestCommitteeErrorEstimate()
public double getBestCommitteeLLEstimate()
public java.lang.String toString()
public static void main(java.lang.String[] argv)
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