weka.classifiers.trees
Class J48

java.lang.Object
  extended by weka.classifiers.Classifier
      extended by weka.classifiers.trees.J48
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

Field Summary
 
Fields inherited from interface weka.core.Drawable
BayesNet, Newick, NOT_DRAWABLE, TREE
 
Constructor Summary
J48()
           
 
Method Summary
 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.util.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(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.
 boolean getSaveInstanceData()
          Check whether instance data is to be saved.
 int getSeed()
          Get the value of Seed.
 boolean getSubtreeRaising()
          Get the value of subtreeRaising.
 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 getUseLaplace()
          Get the value of useLaplace.
 java.lang.String globalInfo()
          Returns a string describing classifier
 java.lang.String graph()
          Returns graph describing the tree.
 int graphType()
          Returns the type of graph this classifier represents.
 java.util.Enumeration listOptions()
          Returns an enumeration describing the available options.
static void main(java.lang.String[] argv)
          Main method for testing this class
 double measureNumLeaves()
          Returns the number of leaves
 double measureNumRules()
          Returns the number of rules (same as number of leaves)
 double measureTreeSize()
          Returns the size of the tree
 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 prefix()
          Returns tree in prefix order.
 java.lang.String reducedErrorPruningTipText()
          Returns the tip text for this property
 java.lang.String saveInstanceDataTipText()
          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 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 setSaveInstanceData(boolean v)
          Set whether instance data is to be saved.
 void setSeed(int newSeed)
          Set the value of Seed.
 void setSubtreeRaising(boolean v)
          Set the value of subtreeRaising.
 void setUnpruned(boolean v)
          Set the value of unpruned.
 void setUseLaplace(boolean newuseLaplace)
          Set the value of useLaplace.
 java.lang.String subtreeRaisingTipText()
          Returns the tip text for this property
 java.lang.String toSource(java.lang.String className)
          Returns tree as an if-then statement.
 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 useLaplaceTipText()
          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

J48

public J48()
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 CapabilitiesHandler
Overrides:
getCapabilities in class Classifier
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 class Classifier
Parameters:
instances - the data to train the classifier 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.

Overrides:
classifyInstance in class Classifier
Parameters:
instance - the instance to classify
Returns:
the classification for the instance
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.

Overrides:
distributionForInstance in class Classifier
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

graphType

public int graphType()
Returns the type of graph this classifier represents.

Specified by:
graphType in interface Drawable
Returns:
Drawable.TREE

graph

public java.lang.String graph()
                       throws java.lang.Exception
Returns graph describing the tree.

Specified by:
graph in interface Drawable
Returns:
the graph describing the tree
Throws:
java.lang.Exception - if graph can't be computed

prefix

public java.lang.String prefix()
                        throws java.lang.Exception
Returns tree in prefix order.

Specified by:
prefix in interface Matchable
Returns:
the tree in prefix order
Throws:
java.lang.Exception - if something goes wrong

toSource

public java.lang.String toSource(java.lang.String className)
                          throws java.lang.Exception
Returns tree as an if-then statement.

Specified by:
toSource in interface Sourcable
Parameters:
className - the name of the Java class
Returns:
the tree as a Java if-then type statement
Throws:
java.lang.Exception - if something goes wrong

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:
listOptions in interface OptionHandler
Overrides:
listOptions in class Classifier
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:

 -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:
setOptions in interface OptionHandler
Overrides:
setOptions in class Classifier
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 Classifier
Returns:
an array of strings suitable for passing to setOptions

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.

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

getUseLaplace

public boolean getUseLaplace()
Get the value of useLaplace.

Returns:
Value of useLaplace.

setUseLaplace

public void setUseLaplace(boolean newuseLaplace)
Set the value of useLaplace.

Parameters:
newuseLaplace - Value to assign to useLaplace.

toString

public java.lang.String toString()
Returns a description of the classifier.

Overrides:
toString in class java.lang.Object
Returns:
a description of the classifier

toSummaryString

public java.lang.String toSummaryString()
Returns a superconcise version of the model

Specified by:
toSummaryString in interface Summarizable
Returns:
a summary of the model

measureTreeSize

public double measureTreeSize()
Returns the size of the tree

Returns:
the size of the tree

measureNumLeaves

public double measureNumLeaves()
Returns the number of leaves

Returns:
the number of leaves

measureNumRules

public double measureNumRules()
Returns the number of rules (same as number of leaves)

Returns:
the number of rules

enumerateMeasures

public java.util.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(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

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 v)
Set the value of unpruned. Turns reduced-error pruning off if set.

Parameters:
v - Value to assign to unpruned.

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. Turns unpruned trees off if set.

Parameters:
v - Value to assign to reducedErrorPruning.

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.

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.

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

getSubtreeRaising

public boolean getSubtreeRaising()
Get the value of subtreeRaising.

Returns:
Value of subtreeRaising.

setSubtreeRaising

public void setSubtreeRaising(boolean v)
Set the value of subtreeRaising.

Parameters:
v - Value to assign to subtreeRaising.

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

getSaveInstanceData

public boolean getSaveInstanceData()
Check whether instance data is to be saved.

Returns:
true if instance data is saved

setSaveInstanceData

public void setSaveInstanceData(boolean v)
Set whether instance data is to be saved.

Parameters:
v - true if instance data is to be saved

getRevision

public java.lang.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(java.lang.String[] argv)
Main method for testing this class

Parameters:
argv - the commandline options