IterativeClassifierOptimizer (weka-dev 3.7.12 API)

java.lang.Object
- weka.classifiers.AbstractClassifier
- - weka.classifiers.RandomizableClassifier
  - - weka.classifiers.meta.IterativeClassifierOptimizer

All Implemented Interfaces:: Serializable, Cloneable, Classifier, AdditionalMeasureProducer, CapabilitiesHandler, CapabilitiesIgnorer, OptionHandler, Randomizable, RevisionHandler

public class IterativeClassifierOptimizer
extends RandomizableClassifier
implements AdditionalMeasureProducer

Chooses the best number of iterations for an IterativeClassifier such as LogitBoost using cross-validation. Optimizes the number of iterations of the given iterative classifier using cross-validation.

Valid options are:

 -A
  If set, average estimate is used rather than one estimate from pooled predictions.

 -L <num>
  The number of iterations to look ahead for to find a better optimum.
  (default 50)

 -P <int>
  The size of the thread pool, for example, the number of cores in the CPU.
  (default 1)

 -E <int>
  The number of threads to use, which should be >= size of thread pool.
  (default 1)

 -I <num>
  Step size for the evaluation, if evaluation is time consuming.
  (default 1)

 -F <num>
  Number of folds for cross-validation.
  (default 10)

 -R <num>
  Number of runs for cross-validation.
  (default 1)

 -W
  Full name of base classifier.
  (default: weka.classifiers.meta.LogitBoost)

 -metric <name>
  Evaluation metric to optimise (default rmse). Available metrics:
  correct,incorrect,kappa,total cost,average cost,kb relative,kb information,
  correlation,complexity 0,complexity scheme,complexity improvement,
  mae,rmse,rae,rrse,coverage,region size,tp rate,fp rate,precision,recall,
  f-measure,mcc,roc area,prc area

 -class-value-index <0-based index>
  Class value index to optimise. Ignored for all but information-retrieval
  type metrics (such as roc area). If unspecified (or a negative value is supplied),
  and an information-retrieval metric is specified, then the class-weighted average
  metric used. (default -1)

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

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

 -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).

 
 Options specific to classifier weka.classifiers.meta.LogitBoost:

 -Q
  Use resampling instead of reweighting for boosting.

 -P <percent>
  Percentage of weight mass to base training on.
  (default 100, reduce to around 90 speed up)

 -L <num>
  Threshold on the improvement of the likelihood.
  (default -Double.MAX_VALUE)

 -H <num>
  Shrinkage parameter.
  (default 1)

 -Z <num>
  Z max threshold for responses.
  (default 3)

 -O <int>
  The size of the thread pool, for example, the number of cores in the CPU. (default 1)

 -E <int>
  The number of threads to use for batch prediction, which should be >= size of thread pool.
  (default 1)

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

 -I <num>
  Number of iterations.
  (default 10)

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

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

 -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).

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

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

 -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).

Version:: $Revision: 10141 $
Author:: Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:: Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

static Tag[] TAGS_EVAL

Fields
Modifier and Type	Field and Description
`static Tag[]`	`TAGS_EVAL`

Constructor Summary

Constructors
Constructor and Description

IterativeClassifierOptimizer()

Constructors
Constructor and Description
`IterativeClassifierOptimizer()`

Method Summary

Methods
Modifier and Type	Method and Description
`void`	`buildClassifier(Instances data)` Builds the classifier.
`String`	`classValueIndexTipText()` Returns the tip text for this property
`double[]`	`distributionForInstance(Instance inst)` Returns the class distribution for an instance.
`Enumeration<String>`	`enumerateMeasures()` Returns an enumeration of the additional measure names
`String`	`evaluationMetricTipText()` Returns the tip text for this property
`Capabilities`	`getCapabilities()` Returns default capabilities of the base classifier.
`int`	`getClassValueIndex()` Get the class value index to use
`SelectedTag`	`getEvaluationMetric()` Get the evaluation metric to use
`IterativeClassifier`	`getIterativeClassifier()` Get the classifier used as the base learner.
`int`	`getLookAheadIterations()` Get the value of LookAheadIterations.
`double`	`getMeasure(String additionalMeasureName)` Returns the value of the named measure
`int`	`getNumFolds()` Get the value of NumFolds.
`int`	`getNumRuns()` Get the value of NumRuns.
`int`	`getNumThreads()` Gets the number of threads.
`String[]`	`getOptions()` Gets the current settings of the Classifier.
`int`	`getPoolSize()` Gets the number of threads.
`String`	`getRevision()` Returns the revision string.
`int`	`getStepSize()` Get the value of StepSize.
`boolean`	`getUseAverage()` Get the value of UseAverage.
`String`	`globalInfo()` Returns a string describing classifier
`String`	`iterativeClassifierTipText()` Returns the tip text for this property
`Enumeration<Option>`	`listOptions()` Returns an enumeration describing the available options.
`String`	`lookAheadIterationsTipText()` Returns the tip text for this property
`static void`	`main(String[] argv)` Main method for testing this class.
`double`	`measureBestNumIts()` Returns the best number of iterations
`double`	`measureBestVal()` Returns the measure for the best model
`String`	`numFoldsTipText()` Returns the tip text for this property
`String`	`numRunsTipText()` Returns the tip text for this property
`String`	`numThreadsTipText()`
`String`	`poolSizeTipText()`
`void`	`setClassValueIndex(int i)` Set the class value index to use
`void`	`setEvaluationMetric(SelectedTag metric)` Set the evaluation metric to use
`void`	`setIterativeClassifier(IterativeClassifier newIterativeClassifier)` Set the base learner.
`void`	`setLookAheadIterations(int newLookAheadIterations)` Set the value of LookAheadIterations.
`void`	`setNumFolds(int newNumFolds)` Set the value of NumFolds.
`void`	`setNumRuns(int newNumRuns)` Set the value of NumRuns.
`void`	`setNumThreads(int nT)` Sets the number of threads
`void`	`setOptions(String[] options)` Parses a given list of options.
`void`	`setPoolSize(int nT)` Sets the number of threads
`void`	`setStepSize(int newStepSize)` Set the value of StepSize.
`void`	`setUseAverage(boolean newUseAverage)` Set the value of UseAverage.
`String`	`stepSizeTipText()` Returns the tip text for this property
`String`	`toString()` Returns a string describing the classifier.
`String`	`useAverageTipText()` Returns the tip text for this property

Methods inherited from class weka.classifiers.RandomizableClassifier
getSeed, seedTipText, setSeed

Methods inherited from class weka.classifiers.AbstractClassifier
classifyInstance, debugTipText, doNotCheckCapabilitiesTipText, forName, getDebug, getDoNotCheckCapabilities, makeCopies, makeCopy, runClassifier, setDebug, setDoNotCheckCapabilities

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Field Detail
  - TAGS_EVAL
```
public static Tag[] TAGS_EVAL
```
- Constructor Detail
  - IterativeClassifierOptimizer
```
public IterativeClassifierOptimizer()
```
- Method Detail
  - globalInfo
```
public String globalInfo()
```
    Returns a string describing classifier
    
    Returns:
    a description suitable for displaying in the explorer/experimenter gui
  - useAverageTipText
```
public String useAverageTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getUseAverage
```
public boolean getUseAverage()
```
    Get the value of UseAverage.
    
    Returns:
    Value of UseAverage.
  - setUseAverage
```
public void setUseAverage(boolean newUseAverage)
```
    Set the value of UseAverage.
    
    Parameters:
    newUseAverage - Value to assign to UseAverage.
  - numThreadsTipText
```
public String numThreadsTipText()
```
    Returns:
    a string to describe the option
  - getNumThreads
```
public int getNumThreads()
```
    Gets the number of threads.
  - setNumThreads
```
public void setNumThreads(int nT)
```
    Sets the number of threads
  - poolSizeTipText
```
public String poolSizeTipText()
```
    Returns:
    a string to describe the option
  - getPoolSize
```
public int getPoolSize()
```
    Gets the number of threads.
  - setPoolSize
```
public void setPoolSize(int nT)
```
    Sets the number of threads
  - stepSizeTipText
```
public String stepSizeTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getStepSize
```
public int getStepSize()
```
    Get the value of StepSize.
    
    Returns:
    Value of StepSize.
  - setStepSize
```
public void setStepSize(int newStepSize)
```
    Set the value of StepSize.
    
    Parameters:
    newStepSize - Value to assign to StepSize.
  - numRunsTipText
```
public String numRunsTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getNumRuns
```
public int getNumRuns()
```
    Get the value of NumRuns.
    
    Returns:
    Value of NumRuns.
  - setNumRuns
```
public void setNumRuns(int newNumRuns)
```
    Set the value of NumRuns.
    
    Parameters:
    newNumRuns - Value to assign to NumRuns.
  - numFoldsTipText
```
public String numFoldsTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getNumFolds
```
public int getNumFolds()
```
    Get the value of NumFolds.
    
    Returns:
    Value of NumFolds.
  - setNumFolds
```
public void setNumFolds(int newNumFolds)
```
    Set the value of NumFolds.
    
    Parameters:
    newNumFolds - Value to assign to NumFolds.
  - lookAheadIterationsTipText
```
public String lookAheadIterationsTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getLookAheadIterations
```
public int getLookAheadIterations()
```
    Get the value of LookAheadIterations.
    
    Returns:
    Value of LookAheadIterations.
  - setLookAheadIterations
```
public void setLookAheadIterations(int newLookAheadIterations)
```
    Set the value of LookAheadIterations.
    
    Parameters:
    newLookAheadIterations - Value to assign to LookAheadIterations.
  - buildClassifier
```
public void buildClassifier(Instances data)
                     throws Exception
```
    Builds the classifier.
    
    Specified by:
    
    buildClassifier in interface Classifier
    
    Parameters:
    data - set of instances serving as training data
    
    Throws:
    
    Exception - if the classifier has not been generated successfully
  - distributionForInstance
```
public double[] distributionForInstance(Instance inst)
                                 throws Exception
```
    Returns the class distribution for an instance.
    
    Specified by:
    
    distributionForInstance in interface Classifier
    
    Overrides:
    
    distributionForInstance in class AbstractClassifier
    
    Parameters:
    inst - the instance to be classified
    
    Returns:
    an array containing the estimated membership probabilities of the test instance in each class or the numeric prediction
    
    Throws:
    
    Exception - if distribution could not be computed successfully
  - toString
```
public String toString()
```
    Returns a string describing the classifier.
    
    Overrides:
    
    toString in class Object
  - listOptions
```
public Enumeration<Option> listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Overrides:
    
    listOptions in class RandomizableClassifier
    
    Returns:
    an enumeration of all the available options.
  - setOptions
```
public void setOptions(String[] options)
                throws Exception
```
    Parses a given list of options. Valid options are:
    -W classname
    Specify the full class name of the base learner.
    Options after -- are passed to the designated classifier.
    
    Specified by:
    
    setOptions in interface OptionHandler
    
    Overrides:
    
    setOptions in class RandomizableClassifier
    
    Parameters:
    options - the list of options as an array of strings
    
    Throws:
    
    Exception - if an option is not supported
  - getOptions
```
public String[] getOptions()
```
    Gets the current settings of the Classifier.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Overrides:
    
    getOptions in class RandomizableClassifier
    
    Returns:
    an array of strings suitable for passing to setOptions
  - evaluationMetricTipText
```
public String evaluationMetricTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setEvaluationMetric
```
public void setEvaluationMetric(SelectedTag metric)
```
    Set the evaluation metric to use
    
    Parameters:
    metric - the metric to use
  - getEvaluationMetric
```
public SelectedTag getEvaluationMetric()
```
    Get the evaluation metric to use
    
    Returns:
    the evaluation metric to use
  - classValueIndexTipText
```
public String classValueIndexTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setClassValueIndex
```
public void setClassValueIndex(int i)
```
    Set the class value index to use
    
    Parameters:
    i - the class value index to use
  - getClassValueIndex
```
public int getClassValueIndex()
```
    Get the class value index to use
    
    Returns:
    the class value index to use
  - iterativeClassifierTipText
```
public String iterativeClassifierTipText()
```
    Returns the tip text for this property
    
    Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns default capabilities of the base classifier.
    
    Specified by:
    
    getCapabilities in interface Classifier
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class AbstractClassifier
    
    Returns:
    the capabilities of the base classifier
    See Also:
    Capabilities
  - setIterativeClassifier
```
public void setIterativeClassifier(IterativeClassifier newIterativeClassifier)
```
    Set the base learner.
    
    Parameters:
    newIterativeClassifier - the classifier to use.
  - getIterativeClassifier
```
public IterativeClassifier getIterativeClassifier()
```
    Get the classifier used as the base learner.
    
    Returns:
    the classifier used as the classifier
  - getRevision
```
public String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class AbstractClassifier
    
    Returns:
    the revision
  - measureBestNumIts
```
public double measureBestNumIts()
```
    Returns the best number of iterations
    
    Returns:
    the best number of iterations
  - measureBestVal
```
public double measureBestVal()
```
    Returns the measure for the best model
    
    Returns:
    the number of leaves
  - enumerateMeasures
```
public Enumeration<String> enumerateMeasures()
```
    Returns an enumeration of the additional measure names
    
    Specified by:
    
    enumerateMeasures in interface AdditionalMeasureProducer
    
    Returns:
    an enumeration of the measure names
  - getMeasure
```
public double getMeasure(String additionalMeasureName)
```
    Returns the value of the named measure
    
    Specified by:
    
    getMeasure in interface AdditionalMeasureProducer
    
    Parameters:
    additionalMeasureName - the name of the measure to query for its value
    
    Returns:
    the value of the named measure
    
    Throws:
    
    IllegalArgumentException - if the named measure is not supported
  - main
```
public static void main(String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    argv - the options

Class IterativeClassifierOptimizer

Field Summary

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.RandomizableClassifier

Methods inherited from class weka.classifiers.AbstractClassifier

Methods inherited from class java.lang.Object

Field Detail

TAGS_EVAL

Constructor Detail

IterativeClassifierOptimizer

Method Detail

globalInfo

useAverageTipText

getUseAverage

setUseAverage

numThreadsTipText

getNumThreads

setNumThreads

poolSizeTipText

getPoolSize

setPoolSize

stepSizeTipText

getStepSize

setStepSize

numRunsTipText

getNumRuns

setNumRuns

numFoldsTipText

getNumFolds

setNumFolds

lookAheadIterationsTipText

getLookAheadIterations

setLookAheadIterations

buildClassifier

distributionForInstance

toString

listOptions

setOptions

getOptions

evaluationMetricTipText

setEvaluationMetric

getEvaluationMetric

classValueIndexTipText

setClassValueIndex

getClassValueIndex

iterativeClassifierTipText

getCapabilities

setIterativeClassifier

getIterativeClassifier

getRevision

measureBestNumIts

measureBestVal

enumerateMeasures

getMeasure

main