Package weka.classifiers.trees
Class J48
- java.lang.Object
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- weka.classifiers.Classifier
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- weka.classifiers.trees.J48
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- All Implemented Interfaces:
java.io.Serializable,java.lang.Cloneable,Sourcable,AdditionalMeasureProducer,CapabilitiesHandler,Drawable,Matchable,OptionHandler,RevisionHandler,Summarizable,TechnicalInformationHandler,WeightedInstancesHandler
public class J48 extends Classifier implements OptionHandler, Drawable, Matchable, Sourcable, WeightedInstancesHandler, Summarizable, AdditionalMeasureProducer, TechnicalInformationHandler
Class for generating a pruned or unpruned C4.5 decision tree. For more information, see
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA. BibTeX:@book{Quinlan1993, address = {San Mateo, CA}, author = {Ross Quinlan}, publisher = {Morgan Kaufmann Publishers}, title = {C4.5: Programs for Machine Learning}, year = {1993} }Valid options are:-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances 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.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
- Version:
- $Revision: 1.9 $
- Author:
- Eibe Frank (eibe@cs.waikato.ac.nz)
- See Also:
- Serialized Form
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Field Summary
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Fields inherited from interface weka.core.Drawable
BayesNet, Newick, NOT_DRAWABLE, TREE
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Constructor Summary
Constructors Constructor Description J48()
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description java.lang.StringbinarySplitsTipText()Returns the tip text for this propertyvoidbuildClassifier(Instances instances)Generates the classifier.doubleclassifyInstance(Instance instance)Classifies an instance.java.lang.StringconfidenceFactorTipText()Returns the tip text for this propertydouble[]distributionForInstance(Instance instance)Returns class probabilities for an instance.java.util.EnumerationenumerateMeasures()Returns an enumeration of the additional measure namesbooleangetBinarySplits()Get the value of binarySplits.CapabilitiesgetCapabilities()Returns default capabilities of the classifier.floatgetConfidenceFactor()Get the value of CF.doublegetMeasure(java.lang.String additionalMeasureName)Returns the value of the named measureintgetMinNumObj()Get the value of minNumObj.intgetNumFolds()Get the value of numFolds.java.lang.String[]getOptions()Gets the current settings of the Classifier.booleangetReducedErrorPruning()Get the value of reducedErrorPruning.java.lang.StringgetRevision()Returns the revision string.booleangetSaveInstanceData()Check whether instance data is to be saved.intgetSeed()Get the value of Seed.booleangetSubtreeRaising()Get the value of subtreeRaising.TechnicalInformationgetTechnicalInformation()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.booleangetUnpruned()Get the value of unpruned.booleangetUseLaplace()Get the value of useLaplace.java.lang.StringglobalInfo()Returns a string describing classifierjava.lang.Stringgraph()Returns graph describing the tree.intgraphType()Returns the type of graph this classifier represents.java.util.EnumerationlistOptions()Returns an enumeration describing the available options.static voidmain(java.lang.String[] argv)Main method for testing this classdoublemeasureNumLeaves()Returns the number of leavesdoublemeasureNumRules()Returns the number of rules (same as number of leaves)doublemeasureTreeSize()Returns the size of the treejava.lang.StringminNumObjTipText()Returns the tip text for this propertyjava.lang.StringnumFoldsTipText()Returns the tip text for this propertyjava.lang.Stringprefix()Returns tree in prefix order.java.lang.StringreducedErrorPruningTipText()Returns the tip text for this propertyjava.lang.StringsaveInstanceDataTipText()Returns the tip text for this propertyjava.lang.StringseedTipText()Returns the tip text for this propertyvoidsetBinarySplits(boolean v)Set the value of binarySplits.voidsetConfidenceFactor(float v)Set the value of CF.voidsetMinNumObj(int v)Set the value of minNumObj.voidsetNumFolds(int v)Set the value of numFolds.voidsetOptions(java.lang.String[] options)Parses a given list of options.voidsetReducedErrorPruning(boolean v)Set the value of reducedErrorPruning.voidsetSaveInstanceData(boolean v)Set whether instance data is to be saved.voidsetSeed(int newSeed)Set the value of Seed.voidsetSubtreeRaising(boolean v)Set the value of subtreeRaising.voidsetUnpruned(boolean v)Set the value of unpruned.voidsetUseLaplace(boolean newuseLaplace)Set the value of useLaplace.java.lang.StringsubtreeRaisingTipText()Returns the tip text for this propertyjava.lang.StringtoSource(java.lang.String className)Returns tree as an if-then statement.java.lang.StringtoString()Returns a description of the classifier.java.lang.StringtoSummaryString()Returns a superconcise version of the modeljava.lang.StringunprunedTipText()Returns the tip text for this propertyjava.lang.StringuseLaplaceTipText()Returns the tip text for this property-
Methods inherited from class weka.classifiers.Classifier
debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
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Method Detail
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globalInfo
public java.lang.String globalInfo()
Returns a string describing classifier- Returns:
- a description suitable for displaying in the explorer/experimenter gui
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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:
getTechnicalInformationin interfaceTechnicalInformationHandler- Returns:
- the technical information about this class
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getCapabilities
public Capabilities getCapabilities()
Returns default capabilities of the classifier.- Specified by:
getCapabilitiesin interfaceCapabilitiesHandler- Overrides:
getCapabilitiesin classClassifier- Returns:
- the capabilities of this classifier
- See Also:
Capabilities
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buildClassifier
public void buildClassifier(Instances instances) throws java.lang.Exception
Generates the classifier.- Specified by:
buildClassifierin classClassifier- Parameters:
instances- the data to train the classifier with- Throws:
java.lang.Exception- if classifier can't be built successfully
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classifyInstance
public double classifyInstance(Instance instance) throws java.lang.Exception
Classifies an instance.- Overrides:
classifyInstancein classClassifier- Parameters:
instance- the instance to classify- Returns:
- the classification for the instance
- Throws:
java.lang.Exception- if instance can't be classified successfully
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distributionForInstance
public final double[] distributionForInstance(Instance instance) throws java.lang.Exception
Returns class probabilities for an instance.- Overrides:
distributionForInstancein classClassifier- Parameters:
instance- the instance to calculate the class probabilities for- Returns:
- the class probabilities
- Throws:
java.lang.Exception- if distribution can't be computed successfully
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graphType
public int graphType()
Returns the type of graph this classifier represents.
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graph
public java.lang.String graph() throws java.lang.ExceptionReturns graph describing the tree.
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prefix
public java.lang.String prefix() throws java.lang.ExceptionReturns tree in prefix order.
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toSource
public java.lang.String toSource(java.lang.String className) throws java.lang.ExceptionReturns tree as an if-then statement.
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listOptions
public java.util.Enumeration listOptions()
Returns an enumeration describing the available options. Valid options are:-U
Use unpruned tree.-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. No subtree raising is performed.-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.-S
Don't perform subtree raising.-L
Do not clean up after the tree has been built. -A
If set, Laplace smoothing is used for predicted probabilites.-Q
The seed for reduced-error pruning.- Specified by:
listOptionsin interfaceOptionHandler- Overrides:
listOptionsin classClassifier- Returns:
- an enumeration of all the available options.
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setOptions
public void setOptions(java.lang.String[] options) throws java.lang.ExceptionParses a given list of options. Valid options are:-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances 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.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
- Specified by:
setOptionsin interfaceOptionHandler- Overrides:
setOptionsin classClassifier- Parameters:
options- the list of options as an array of strings- Throws:
java.lang.Exception- if an option is not supported
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getOptions
public java.lang.String[] getOptions()
Gets the current settings of the Classifier.- Specified by:
getOptionsin interfaceOptionHandler- Overrides:
getOptionsin classClassifier- Returns:
- an array of strings suitable for passing to setOptions
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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
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getSeed
public int getSeed()
Get the value of Seed.- Returns:
- Value of Seed.
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setSeed
public void setSeed(int newSeed)
Set the value of Seed.- Parameters:
newSeed- Value to assign to Seed.
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useLaplaceTipText
public java.lang.String useLaplaceTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getUseLaplace
public boolean getUseLaplace()
Get the value of useLaplace.- Returns:
- Value of useLaplace.
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setUseLaplace
public void setUseLaplace(boolean newuseLaplace)
Set the value of useLaplace.- Parameters:
newuseLaplace- Value to assign to useLaplace.
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toString
public java.lang.String toString()
Returns a description of the classifier.- Overrides:
toStringin classjava.lang.Object- Returns:
- a description of the classifier
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toSummaryString
public java.lang.String toSummaryString()
Returns a superconcise version of the model- Specified by:
toSummaryStringin interfaceSummarizable- Returns:
- a summary of the model
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measureTreeSize
public double measureTreeSize()
Returns the size of the tree- Returns:
- the size of the tree
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measureNumLeaves
public double measureNumLeaves()
Returns the number of leaves- Returns:
- the number of leaves
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measureNumRules
public double measureNumRules()
Returns the number of rules (same as number of leaves)- Returns:
- the number of rules
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enumerateMeasures
public java.util.Enumeration enumerateMeasures()
Returns an enumeration of the additional measure names- Specified by:
enumerateMeasuresin interfaceAdditionalMeasureProducer- Returns:
- an enumeration of the measure names
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getMeasure
public double getMeasure(java.lang.String additionalMeasureName)
Returns the value of the named measure- Specified by:
getMeasurein interfaceAdditionalMeasureProducer- 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
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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
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getUnpruned
public boolean getUnpruned()
Get the value of unpruned.- Returns:
- Value of unpruned.
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setUnpruned
public void setUnpruned(boolean v)
Set the value of unpruned. Turns reduced-error pruning off if set.- Parameters:
v- Value to assign to unpruned.
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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
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getConfidenceFactor
public float getConfidenceFactor()
Get the value of CF.- Returns:
- Value of CF.
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setConfidenceFactor
public void setConfidenceFactor(float v)
Set the value of CF.- Parameters:
v- Value to assign to CF.
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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
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getMinNumObj
public int getMinNumObj()
Get the value of minNumObj.- Returns:
- Value of minNumObj.
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setMinNumObj
public void setMinNumObj(int v)
Set the value of minNumObj.- Parameters:
v- Value to assign to minNumObj.
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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
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getReducedErrorPruning
public boolean getReducedErrorPruning()
Get the value of reducedErrorPruning.- Returns:
- Value of reducedErrorPruning.
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setReducedErrorPruning
public void setReducedErrorPruning(boolean v)
Set the value of reducedErrorPruning. Turns unpruned trees off if set.- Parameters:
v- Value to assign to reducedErrorPruning.
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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
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getNumFolds
public int getNumFolds()
Get the value of numFolds.- Returns:
- Value of numFolds.
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setNumFolds
public void setNumFolds(int v)
Set the value of numFolds.- Parameters:
v- Value to assign to numFolds.
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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
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getBinarySplits
public boolean getBinarySplits()
Get the value of binarySplits.- Returns:
- Value of binarySplits.
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setBinarySplits
public void setBinarySplits(boolean v)
Set the value of binarySplits.- Parameters:
v- Value to assign to binarySplits.
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subtreeRaisingTipText
public java.lang.String subtreeRaisingTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getSubtreeRaising
public boolean getSubtreeRaising()
Get the value of subtreeRaising.- Returns:
- Value of subtreeRaising.
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setSubtreeRaising
public void setSubtreeRaising(boolean v)
Set the value of subtreeRaising.- Parameters:
v- Value to assign to subtreeRaising.
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saveInstanceDataTipText
public java.lang.String saveInstanceDataTipText()
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getSaveInstanceData
public boolean getSaveInstanceData()
Check whether instance data is to be saved.- Returns:
- true if instance data is saved
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setSaveInstanceData
public void setSaveInstanceData(boolean v)
Set whether instance data is to be saved.- Parameters:
v- true if instance data is to be saved
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getRevision
public java.lang.String getRevision()
Returns the revision string.- Specified by:
getRevisionin interfaceRevisionHandler- Overrides:
getRevisionin classClassifier- Returns:
- the revision
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main
public static void main(java.lang.String[] argv)
Main method for testing this class- Parameters:
argv- the commandline options
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