PART

java.lang.Object
- weka.classifiers.AbstractClassifier
- - weka.classifiers.rules.PART

All Implemented Interfaces:: java.io.Serializable, java.lang.Cloneable, Classifier, AdditionalMeasureProducer, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, RevisionHandler, Summarizable, TechnicalInformationHandler, WeightedInstancesHandler

public class PART
extends AbstractClassifier
implements OptionHandler, WeightedInstancesHandler, Summarizable, AdditionalMeasureProducer, TechnicalInformationHandler

Class for generating a PART decision list. Uses separate-and-conquer. Builds a partial C4.5 decision tree in each iteration and makes the "best" leaf into a rule.

For more information, see:

Eibe Frank, Ian H. Witten: Generating Accurate Rule Sets Without Global Optimization. In: Fifteenth International Conference on Machine Learning, 144-151, 1998.

BibTeX:

 @inproceedings{Frank1998,
    author = {Eibe Frank and Ian H. Witten},
    booktitle = {Fifteenth International Conference on Machine Learning},
    editor = {J. Shavlik},
    pages = {144-151},
    publisher = {Morgan Kaufmann},
    title = {Generating Accurate Rule Sets Without Global Optimization},
    year = {1998},
    PS = {http://www.cs.waikato.ac.nz/\~eibe/pubs/ML98-57.ps.gz}
 }

Valid options are:

 -C <pruning confidence>
  Set confidence threshold for pruning.
  (default 0.25)

 -M <minimum number of objects>
  Set minimum number of objects per leaf.
  (default 2)

 -R
  Use reduced error pruning.

 -N <number of folds>
  Set number of folds for reduced error
  pruning. One fold is used as pruning set.
  (default 3)

 -B
  Use binary splits only.

 -U
  Generate unpruned decision list.

 -J
  Do not use MDL correction for info gain on numeric attributes.

 -Q <seed>
  Seed for random data shuffling (default 1).

 -doNotMakeSplitPointActualValue
  Do not make split point actual value.

Version:: $Revision: 15233 $
Author:: Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:: Serialized Form

Field Summary
- Fields inherited from class weka.classifiers.AbstractClassifier
  BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT

Constructor Summary

Constructors
Constructor and Description

PART()

Constructors
Constructor and Description
`PART()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`java.lang.String`	`binarySplitsTipText()` Returns the tip text for this property
`void`	`buildClassifier(Instances instances)` Generates the classifier.
`double`	`classifyInstance(Instance instance)` Classifies an instance.
`java.lang.String`	`confidenceFactorTipText()` Returns the tip text for this property
`double[]`	`distributionForInstance(Instance instance)` Returns class probabilities for an instance.
`java.lang.String`	`doNotMakeSplitPointActualValueTipText()` Returns the tip text for this property
`java.util.Enumeration<java.lang.String>`	`enumerateMeasures()` Returns an enumeration of the additional measure names
`boolean`	`getBinarySplits()` Get the value of binarySplits.
`Capabilities`	`getCapabilities()` Returns default capabilities of the classifier.
`float`	`getConfidenceFactor()` Get the value of CF.
`boolean`	`getDoNotMakeSplitPointActualValue()` Gets the value of doNotMakeSplitPointActualValue.
`double`	`getMeasure(java.lang.String additionalMeasureName)` Returns the value of the named measure
`int`	`getMinNumObj()` Get the value of minNumObj.
`int`	`getNumFolds()` Get the value of numFolds.
`java.lang.String[]`	`getOptions()` Gets the current settings of the Classifier.
`boolean`	`getReducedErrorPruning()` Get the value of reducedErrorPruning.
`java.lang.String`	`getRevision()` Returns the revision string.
`int`	`getSeed()` Get the value of Seed.
`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`	`getUnpruned()` Get the value of unpruned.
`boolean`	`getUseMDLcorrection()` Get the value of useMDLcorrection.
`java.lang.String`	`globalInfo()` Returns a string describing classifier
`java.util.Enumeration<Option>`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(java.lang.String[] argv)` Main method for testing this class.
`double`	`measureNumRules()` Return the number of rules.
`java.lang.String`	`minNumObjTipText()` Returns the tip text for this property
`java.lang.String`	`numFoldsTipText()` Returns the tip text for this property
`java.lang.String`	`reducedErrorPruningTipText()` Returns the tip text for this property
`java.lang.String`	`seedTipText()` Returns the tip text for this property
`void`	`setBinarySplits(boolean v)` Set the value of binarySplits.
`void`	`setConfidenceFactor(float v)` Set the value of CF.
`void`	`setDoNotMakeSplitPointActualValue(boolean m_doNotMakeSplitPointActualValue)` Sets the value of doNotMakeSplitPointActualValue.
`void`	`setMinNumObj(int v)` Set the value of minNumObj.
`void`	`setNumFolds(int v)` Set the value of numFolds.
`void`	`setOptions(java.lang.String[] options)` Parses a given list of options.
`void`	`setReducedErrorPruning(boolean v)` Set the value of reducedErrorPruning.
`void`	`setSeed(int newSeed)` Set the value of Seed.
`void`	`setUnpruned(boolean newunpruned)` Set the value of unpruned.
`void`	`setUseMDLcorrection(boolean newuseMDLcorrection)` Set the value of useMDLcorrection.
`java.lang.String`	`toString()` Returns a description of the classifier
`java.lang.String`	`toSummaryString()` Returns a superconcise version of the model
`java.lang.String`	`unprunedTipText()` Returns the tip text for this property
`java.lang.String`	`useMDLcorrectionTipText()` Returns the tip text for this property

Methods inherited from class weka.classifiers.AbstractClassifier
batchSizeTipText, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

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

Methods inherited from interface weka.core.OptionHandler
makeCopy

- Constructor Detail
  - PART
```
public PART()
```
- Method Detail
  - globalInfo
```
public java.lang.String globalInfo()
```
    Returns a string describing classifier
    
    Returns:
    
    a description 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
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns default capabilities of the classifier.
    
    Specified by:
    
    getCapabilities in interface Classifier
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class AbstractClassifier
    
    Returns:
    
    the capabilities of this classifier
    
    See Also:
    
    Capabilities
  - buildClassifier
```
public void buildClassifier(Instances instances)
                     throws java.lang.Exception
```
    Generates the classifier.
    
    Specified by:
    
    buildClassifier in interface Classifier
    
    Parameters:
    
    instances - the data to train with
    
    Throws:
    
    java.lang.Exception - if classifier can't be built successfully
  - classifyInstance
```
public double classifyInstance(Instance instance)
                        throws java.lang.Exception
```
    Classifies an instance.
    
    Specified by:
    
    classifyInstance in interface Classifier
    
    Overrides:
    
    classifyInstance in class AbstractClassifier
    
    Parameters:
    
    instance - the instance to classify
    
    Returns:
    
    the classification
    
    Throws:
    
    java.lang.Exception - if instance can't be classified successfully
  - distributionForInstance
```
public final double[] distributionForInstance(Instance instance)
                                       throws java.lang.Exception
```
    Returns class probabilities for an instance.
    
    Specified by:
    
    distributionForInstance in interface Classifier
    
    Overrides:
    
    distributionForInstance in class AbstractClassifier
    
    Parameters:
    
    instance - the instance to get the distribution for
    
    Returns:
    
    the class probabilities
    
    Throws:
    
    java.lang.Exception - if the distribution can't be computed successfully
  - listOptions
```
public java.util.Enumeration<Option> listOptions()
```
    Returns an enumeration describing the available options. Valid options are:
    -C confidence
    Set confidence threshold for pruning. (Default: 0.25)
    -M number
    Set minimum number of instances per leaf. (Default: 2)
    -R
    Use reduced error pruning.
    -N number
    Set number of folds for reduced error pruning. One fold is used as the pruning set. (Default: 3)
    -B
    Use binary splits for nominal attributes.
    -U
    Generate unpruned decision list.
    -Q
    The seed for reduced-error pruning.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Overrides:
    
    listOptions in class AbstractClassifier
    
    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 <pruning confidence>
  Set confidence threshold for pruning.
  (default 0.25)
 
```
```
 -M <minimum number of objects>
  Set minimum number of objects per leaf.
  (default 2)
 
```
```
 -R
  Use reduced error pruning.
 
```
```
 -N <number of folds>
  Set number of folds for reduced error
  pruning. One fold is used as pruning set.
  (default 3)
 
```
```
 -B
  Use binary splits only.
 
```
```
 -U
  Generate unpruned decision list.
 
```
```
 -J
  Do not use MDL correction for info gain on numeric attributes.
 
```
```
 -Q <seed>
  Seed for random data shuffling (default 1).
 
```
```
 -doNotMakeSplitPointActualValue
  Do not make split point actual value.
 
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Overrides:
    
    setOptions in class AbstractClassifier
    
    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 AbstractClassifier
    
    Returns:
    
    an array of strings suitable for passing to setOptions
  - toString
```
public java.lang.String toString()
```
    Returns a description of the classifier
    
    Overrides:
    
    toString in class java.lang.Object
    
    Returns:
    
    a string representation of the classifier
  - toSummaryString
```
public java.lang.String toSummaryString()
```
    Returns a superconcise version of the model
    
    Specified by:
    
    toSummaryString in interface Summarizable
    
    Returns:
    
    a concise version of the model
  - measureNumRules
```
public double measureNumRules()
```
    Return the number of rules.
    
    Returns:
    
    the number of rules
  - enumerateMeasures
```
public java.util.Enumeration<java.lang.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(java.lang.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:
    
    java.lang.IllegalArgumentException - if the named measure is not supported
  - confidenceFactorTipText
```
public java.lang.String confidenceFactorTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getConfidenceFactor
```
public float getConfidenceFactor()
```
    Get the value of CF.
    
    Returns:
    
    Value of CF.
  - setConfidenceFactor
```
public void setConfidenceFactor(float v)
```
    Set the value of CF.
    
    Parameters:
    
    v - Value to assign to CF.
  - minNumObjTipText
```
public java.lang.String minNumObjTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getMinNumObj
```
public int getMinNumObj()
```
    Get the value of minNumObj.
    
    Returns:
    
    Value of minNumObj.
  - setMinNumObj
```
public void setMinNumObj(int v)
```
    Set the value of minNumObj.
    
    Parameters:
    
    v - Value to assign to minNumObj.
  - reducedErrorPruningTipText
```
public java.lang.String reducedErrorPruningTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getReducedErrorPruning
```
public boolean getReducedErrorPruning()
```
    Get the value of reducedErrorPruning.
    
    Returns:
    
    Value of reducedErrorPruning.
  - setReducedErrorPruning
```
public void setReducedErrorPruning(boolean v)
```
    Set the value of reducedErrorPruning.
    
    Parameters:
    
    v - Value to assign to reducedErrorPruning.
  - unprunedTipText
```
public java.lang.String unprunedTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getUnpruned
```
public boolean getUnpruned()
```
    Get the value of unpruned.
    
    Returns:
    
    Value of unpruned.
  - setUnpruned
```
public void setUnpruned(boolean newunpruned)
```
    Set the value of unpruned.
    
    Parameters:
    
    newunpruned - Value to assign to unpruned.
  - useMDLcorrectionTipText
```
public java.lang.String useMDLcorrectionTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getUseMDLcorrection
```
public boolean getUseMDLcorrection()
```
    Get the value of useMDLcorrection.
    
    Returns:
    
    Value of useMDLcorrection.
  - setUseMDLcorrection
```
public void setUseMDLcorrection(boolean newuseMDLcorrection)
```
    Set the value of useMDLcorrection.
    
    Parameters:
    
    newuseMDLcorrection - Value to assign to useMDLcorrection.
  - numFoldsTipText
```
public java.lang.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 v)
```
    Set the value of numFolds.
    
    Parameters:
    
    v - Value to assign to numFolds.
  - seedTipText
```
public java.lang.String seedTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getSeed
```
public int getSeed()
```
    Get the value of Seed.
    
    Returns:
    
    Value of Seed.
  - setSeed
```
public void setSeed(int newSeed)
```
    Set the value of Seed.
    
    Parameters:
    
    newSeed - Value to assign to Seed.
  - binarySplitsTipText
```
public java.lang.String binarySplitsTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getBinarySplits
```
public boolean getBinarySplits()
```
    Get the value of binarySplits.
    
    Returns:
    
    Value of binarySplits.
  - setBinarySplits
```
public void setBinarySplits(boolean v)
```
    Set the value of binarySplits.
    
    Parameters:
    
    v - Value to assign to binarySplits.
  - doNotMakeSplitPointActualValueTipText
```
public java.lang.String doNotMakeSplitPointActualValueTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getDoNotMakeSplitPointActualValue
```
public boolean getDoNotMakeSplitPointActualValue()
```
    Gets the value of doNotMakeSplitPointActualValue.
    
    Returns:
    
    the value
  - setDoNotMakeSplitPointActualValue
```
public void setDoNotMakeSplitPointActualValue(boolean m_doNotMakeSplitPointActualValue)
```
    Sets the value of doNotMakeSplitPointActualValue.
    
    Parameters:
    
    m_doNotMakeSplitPointActualValue - the value to set
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class AbstractClassifier
    
    Returns:
    
    the revision
  - main
```
public static void main(java.lang.String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    
    argv - command line options

Class PART

Field Summary

Fields inherited from class weka.classifiers.AbstractClassifier

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.AbstractClassifier

Methods inherited from class java.lang.Object

Methods inherited from interface weka.core.OptionHandler

Constructor Detail

PART

Method Detail

globalInfo

getTechnicalInformation

getCapabilities

buildClassifier

classifyInstance

distributionForInstance

listOptions

setOptions

getOptions

toString

toSummaryString

measureNumRules

enumerateMeasures

getMeasure

confidenceFactorTipText

getConfidenceFactor

setConfidenceFactor

minNumObjTipText

getMinNumObj

setMinNumObj

reducedErrorPruningTipText

getReducedErrorPruning

setReducedErrorPruning

unprunedTipText

getUnpruned

setUnpruned

useMDLcorrectionTipText

getUseMDLcorrection

setUseMDLcorrection

numFoldsTipText

getNumFolds

setNumFolds

seedTipText

getSeed

setSeed

binarySplitsTipText

getBinarySplits

setBinarySplits

doNotMakeSplitPointActualValueTipText

getDoNotMakeSplitPointActualValue

setDoNotMakeSplitPointActualValue

getRevision

main