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Class weka.classifiers.trees.REPTree

java.lang.Object
    |
    +----weka.classifiers.Classifier
            |
            +----weka.classifiers.DistributionClassifier
                    |
                    +----weka.classifiers.trees.REPTree

public class REPTree

extends DistributionClassifier

implements OptionHandler, WeightedInstancesHandler, Drawable, AdditionalMeasureProducer, Sourcable

-M number
Set minimum number of instances per leaf (default 2).

-V number
Set minimum numeric class variance proportion of train variance for split (default 1e-3).

-N number
Number of folds for reduced error pruning (default 3).

-S number
Seed for random data shuffling (default 1).

-P
No pruning.

-D
Maximum tree depth (default -1, no maximum).

Version:

$Revision: 1.10 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz)

REPTree()

 

buildClassifier(Instances)

Builds classifier.

distributionForInstance(Instance)

Computes class distribution of an instance using the tree.

enumerateMeasures()

Returns an enumeration of the additional measure names.

getMaxDepth()

Get the value of MaxDepth.

getMeasure(String)

Returns the value of the named measure.

getMinNum()

Get the value of MinNum.

getMinVarianceProp()

Get the value of MinVarianceProp.

getNoPruning()

Get the value of NoPruning.

getNumFolds()

Get the value of NumFolds.

getOptions()

Gets options from this classifier.

getSeed()

Get the value of Seed.

graph()

Outputs the decision tree as a graph

listOptions()

Lists the command-line options for this classifier.

main(String[])

Main method for this class.

numNodes()

Computes size of the tree.

setMaxDepth(int)

Set the value of MaxDepth.

setMinNum(double)

Set the value of MinNum.

setMinVarianceProp(double)

Set the value of MinVarianceProp.

setNoPruning(boolean)

Set the value of NoPruning.

setNumFolds(int)

Set the value of NumFolds.

setOptions(String[])

Parses a given list of options.

setSeed(int)

Set the value of Seed.

toSource(String)

Returns the tree as if-then statements.

toString()

Outputs the decision tree.

public REPTree()

public boolean getNoPruning()

          Get the value of NoPruning.

Returns:

Value of NoPruning.

public void setNoPruning(boolean newNoPruning)

          Set the value of NoPruning.

Parameters:

newNoPruning - Value to assign to NoPruning.

public double getMinNum()

          Get the value of MinNum.

Returns:

Value of MinNum.

public void setMinNum(double newMinNum)

          Set the value of MinNum.

Parameters:

newMinNum - Value to assign to MinNum.

public double getMinVarianceProp()

          Get the value of MinVarianceProp.

Returns:

Value of MinVarianceProp.

public void setMinVarianceProp(double newMinVarianceProp)

          Set the value of MinVarianceProp.

Parameters:

newMinVarianceProp - Value to assign to MinVarianceProp.

public int getSeed()

          Get the value of Seed.

Returns:

Value of Seed.

public void setSeed(int newSeed)

          Set the value of Seed.

Parameters:

newSeed - Value to assign to Seed.

public int getNumFolds()

          Get the value of NumFolds.

Returns:

Value of NumFolds.

public void setNumFolds(int newNumFolds)

          Set the value of NumFolds.

Parameters:

newNumFolds - Value to assign to NumFolds.

public int getMaxDepth()

          Get the value of MaxDepth.

Returns:

Value of MaxDepth.

public void setMaxDepth(int newMaxDepth)

          Set the value of MaxDepth.

Parameters:

newMaxDepth - Value to assign to MaxDepth.

public java.util.Enumeration listOptions()

          Lists the command-line options for this classifier.

public java.lang.String[] getOptions()

          Gets options from this classifier.

public void setOptions(java.lang.String options[]) throws java.lang.Exception

          Parses a given list of options.

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

public int numNodes()

          Computes size of the tree.

public java.util.Enumeration enumerateMeasures()

          Returns an enumeration of the additional measure names.

Returns:

an enumeration of the measure names

public double getMeasure(java.lang.String additionalMeasureName)

          Returns the value of the named measure.

Parameters:

measureName - 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

public void buildClassifier(Instances data) throws java.lang.Exception

          Builds classifier.

Overrides:

buildClassifier in class Classifier

public double[] distributionForInstance(Instance instance) throws java.lang.Exception

          Computes class distribution of an instance using the tree.

Overrides:

distributionForInstance in class DistributionClassifier

public java.lang.String toSource(java.lang.String className) throws java.lang.Exception

          Returns the tree as if-then statements.

Returns:

the tree as a Java if-then type statement

Throws:

java.lang.Exception - if something goes wrong

public java.lang.String graph() throws java.lang.Exception

          Outputs the decision tree as a graph

public java.lang.String toString()

          Outputs the decision tree.

Overrides:

toString in class java.lang.Object

public static void main(java.lang.String argv[])

          Main method for this class.

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