PART (weka-stable 3.6.14 API)

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

All Implemented Interfaces:: Serializable, Cloneable, AdditionalMeasureProducer, CapabilitiesHandler, OptionHandler, RevisionHandler, Summarizable, TechnicalInformationHandler, WeightedInstancesHandler

public class PART
extends Classifier
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.

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

Version:: $Revision: 1.10 $
Author:: Eibe Frank ([email protected])
See Also:: Serialized Form

Constructor Summary

Constructors
Constructor and Description

PART()

Constructors
Constructor and Description
`PART()`

Method Summary

Methods
Modifier and Type	Method and Description
`String`	`binarySplitsTipText()` Returns the tip text for this property
`void`	`buildClassifier(Instances instances)` Generates the classifier.
`double`	`classifyInstance(Instance instance)` Classifies an instance.
`String`	`confidenceFactorTipText()` Returns the tip text for this property
`double[]`	`distributionForInstance(Instance instance)` Returns class probabilities for an instance.
`Enumeration`	`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.
`double`	`getMeasure(String additionalMeasureName)` Returns the value of the named measure
`int`	`getMinNumObj()` Get the value of minNumObj.
`int`	`getNumFolds()` Get the value of numFolds.
`String[]`	`getOptions()` Gets the current settings of the Classifier.
`boolean`	`getReducedErrorPruning()` Get the value of reducedErrorPruning.
`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.
`String`	`globalInfo()` Returns a string describing classifier
`Enumeration`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(String[] argv)` Main method for testing this class.
`double`	`measureNumRules()` Return the number of rules.
`String`	`minNumObjTipText()` Returns the tip text for this property
`String`	`numFoldsTipText()` Returns the tip text for this property
`String`	`reducedErrorPruningTipText()` Returns the tip text for this property
`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`	`setMinNumObj(int v)` Set the value of minNumObj.
`void`	`setNumFolds(int v)` Set the value of numFolds.
`void`	`setOptions(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.
`String`	`toString()` Returns a description of the classifier
`String`	`toSummaryString()` Returns a superconcise version of the model
`String`	`unprunedTipText()` Returns the tip text for this property

Methods inherited from class weka.classifiers.Classifier
debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug

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

- Constructor Detail
  - PART
```
public PART()
```
- Method Detail
  - globalInfo
```
public 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 CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class Classifier
    
    Returns:
    the capabilities of this classifier
    See Also:
    Capabilities
  - buildClassifier
```
public void buildClassifier(Instances instances)
                     throws Exception
```
    Generates the classifier.
    
    Specified by:
    
    buildClassifier in class Classifier
    
    Parameters:
    instances - the data to train with
    
    Throws:
    
    Exception - if classifier can't be built successfully
  - classifyInstance
```
public double classifyInstance(Instance instance)
                        throws Exception
```
    Classifies an instance.
    
    Overrides:
    
    classifyInstance in class Classifier
    
    Parameters:
    instance - the instance to classify
    
    Returns:
    the classification
    
    Throws:
    
    Exception - if instance can't be classified successfully
  - distributionForInstance
```
public final double[] distributionForInstance(Instance instance)
                                       throws Exception
```
    Returns class probabilities for an instance.
    
    Overrides:
    
    distributionForInstance in class Classifier
    
    Parameters:
    instance - the instance to get the distribution for
    
    Returns:
    the class probabilities
    
    Throws:
    
    Exception - if the distribution can't be computed successfully
  - listOptions
```
public Enumeration 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 Classifier
    
    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:
```
 -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.
```
```
 -Q <seed>
  Seed for random data shuffling (default 1).
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Overrides:
    
    setOptions in class Classifier
    
    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 Classifier
    
    Returns:
    an array of strings suitable for passing to setOptions
  - toString
```
public String toString()
```
    Returns a description of the classifier
    
    Overrides:
    
    toString in class Object
    
    Returns:
    a string representation of the classifier
  - toSummaryString
```
public 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 Enumeration 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
  - confidenceFactorTipText
```
public 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 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 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 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.
  - 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 v)
```
    Set the value of numFolds.
    
    Parameters:
    v - Value to assign to numFolds.
  - seedTipText
```
public 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 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.
  - getRevision
```
public 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(String[] argv)
```
    Main method for testing this class.
    
    Parameters:
    argv - command line options

Class PART

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.Classifier

Methods inherited from class java.lang.Object

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

numFoldsTipText

getNumFolds

setNumFolds

seedTipText

getSeed

setSeed

binarySplitsTipText

getBinarySplits

setBinarySplits

getRevision

main