weka.classifiers.trees
Class RandomForest

java.lang.Object
  |
  +--weka.classifiers.Classifier
        |
        +--weka.classifiers.trees.RandomForest

All Implemented Interfaces:

AdditionalMeasureProducer, java.lang.Cloneable, OptionHandler, Randomizable, java.io.Serializable, WeightedInstancesHandler

public class RandomForest

extends Classifier

implements OptionHandler, Randomizable, WeightedInstancesHandler, AdditionalMeasureProducer

Class for constructing random forests. For more information see:

Leo Breiman. Random Forests. Machine Learning 45 (1):5-32, October 2001.

Valid options are:

-I num
Set the number of trees in the forest (default 10)

-K num
Set the number of features to consider. If < 1 (the default) will use logM+1, where M is the number of inputs.

-S seed
Random number seed (default 1).

Version:

$Revision: 1.5 $

Author:

Richard Kirkby (rkirkby@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

RandomForest()

Method Summary

void	buildClassifier(Instances data) Builds a classifier for a set of instances.
double[]	distributionForInstance(Instance instance) Returns the class probability distribution for an instance.
java.util.Enumeration	enumerateMeasures() Returns an enumeration of the additional measure names.
double	getMeasure(java.lang.String additionalMeasureName) Returns the value of the named measure.
int	getNumFeatures() Get the number of features used in random selection.
int	getNumTrees() Get the value of numTrees.
java.lang.String[]	getOptions() Gets the current settings of the forest.
int	getSeed() Gets the seed for the random number generations
java.lang.String	globalInfo() Returns a string describing classifier
java.util.Enumeration	listOptions() Returns an enumeration describing the available options.
static void	main(java.lang.String[] argv) Main method for this class.
double	measureOutOfBagError() Gets the out of bag error that was calculated as the classifier was built.
java.lang.String	numFeaturesTipText() Returns the tip text for this property
java.lang.String	numTreesTipText() Returns the tip text for this property
java.lang.String	seedTipText() Returns the tip text for this property
void	setNumFeatures(int newNumFeatures) Set the number of features to use in random selection.
void	setNumTrees(int newNumTrees) Set the value of numTrees.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setSeed(int seed) Set the seed for random number generation.
java.lang.String	toString() Outputs a description of this classifier.

Methods inherited from class weka.classifiers.Classifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, setDebug

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

RandomForest

public RandomForest()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing classifier

Returns:

a description suitable for displaying in the explorer/experimenter gui

numTreesTipText

public java.lang.String numTreesTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getNumTrees

public int getNumTrees()

Get the value of numTrees.

Returns:

Value of numTrees.

setNumTrees

public void setNumTrees(int newNumTrees)

Set the value of numTrees.

Parameters:

newNumTrees - Value to assign to numTrees.

numFeaturesTipText

public java.lang.String numFeaturesTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getNumFeatures

public int getNumFeatures()

Get the number of features used in random selection.

Returns:

Value of numFeatures.

setNumFeatures

public void setNumFeatures(int newNumFeatures)

Set the number of features to use in random selection.

Parameters:

newNumFeatures - Value to assign to numFeatures.

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

setSeed

public void setSeed(int seed)

Set the seed for random number generation.

Specified by:

setSeed in interface Randomizable

Parameters:

seed - the seed

getSeed

public int getSeed()

Gets the seed for the random number generations

Specified by:

getSeed in interface Randomizable

Returns:

the seed for the random number generation

measureOutOfBagError

public double measureOutOfBagError()

Gets the out of bag error that was calculated as the classifier was built.

Returns:

the out of bag error

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

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class Classifier

Returns:

an enumeration of all the available options

getOptions

public java.lang.String[] getOptions()

Gets the current settings of the forest.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class Classifier

Returns:

an array of strings suitable for passing to setOptions()

setOptions

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

Parses a given list of options.

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

buildClassifier

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

Builds a classifier for a set of instances.

Specified by:

buildClassifier in class Classifier

Parameters:

data - set of instances serving as training data

Throws:

java.lang.Exception - if something goes wrong

distributionForInstance

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

Returns the class probability distribution for an instance.

Overrides:

distributionForInstance in class Classifier

Parameters:

instance - the instance to be classified

Returns:

the distribution the forest generates for the instance

Throws:

java.lang.Exception - if distribution could not be computed successfully

toString

public java.lang.String toString()

Outputs a description of this classifier.

Overrides:

toString in class java.lang.Object

Returns:

a string containing a description of the classifier

main

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

Main method for this class.

Parameters:

argv - the options