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

All Implemented Interfaces:: java.io.Serializable, java.lang.Cloneable, AdditionalMeasureProducer, CapabilitiesHandler, OptionHandler, Randomizable, RevisionHandler, TechnicalInformationHandler, WeightedInstancesHandler

public class RandomForest
extends Classifier
implements OptionHandler, Randomizable, WeightedInstancesHandler, AdditionalMeasureProducer, TechnicalInformationHandler

Class for constructing a forest of random trees.

For more information see:

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

BibTeX:

 @article{Breiman2001,
    author = {Leo Breiman},
    journal = {Machine Learning},
    number = {1},
    pages = {5-32},
    title = {Random Forests},
    volume = {45},
    year = {2001}
 }

Valid options are:

 -I <number of trees>
  Number of trees to build.

 -K <number of features>
  Number of features to consider (<0 = int(log_2(#predictors)+1)).

 -S
  Seed for random number generator.
  (default 1)

 -depth <num>
  The maximum depth of the trees, 0 for unlimited.
  (default 0)

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

Version:: $Revision: 1.13 $
Author:: Richard Kirkby (rkirkby@cs.waikato.ac.nz)
See Also:: Serialized Form

Constructor Summary

Constructors
Constructor Description

RandomForest()

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`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.
`Capabilities`	`getCapabilities()`	Returns default capabilities of the classifier.
`int`	`getMaxDepth()`	Get the maximum depth of trh tree, 0 for unlimited.
`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.
`java.lang.String`	`getRevision()`	Returns the revision string.
`int`	`getSeed()`	Gets the seed for the random number generations
`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.
`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.
`java.lang.String`	`maxDepthTipText()`	Returns the tip text for this property
`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`	`setMaxDepth(int value)`	Set the maximum depth of the tree, 0 for unlimited.
`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, makeCopy, 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
  - 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
  - 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
  - maxDepthTipText
```
public java.lang.String maxDepthTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - getMaxDepth
```
public int getMaxDepth()
```
    Get the maximum depth of trh tree, 0 for unlimited.
    
    Returns:
    
    the maximum depth.
  - setMaxDepth
```
public void setMaxDepth(int value)
```
    Set the maximum depth of the tree, 0 for unlimited.
    
    Parameters:
    
    value - the maximum depth.
  - 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.
    Valid options are:
    
    -I <number of trees> Number of trees to build.
    
    -K <number of features> Number of features to consider (<0 = int(log_2(#predictors)+1)).
    
    -S Seed for random number generator. (default 1)
    
    -depth <num> The maximum depth of the trees, 0 for unlimited. (default 0)
    
    -D If set, classifier is run in debug mode and may output additional info to the console
    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
  - 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 data)
                     throws java.lang.Exception
```
    Builds a classifier for a set of instances.
    
    Specified by:
    
    buildClassifier in class Classifier
    
    Parameters:
    
    data - the instances to train the classifier with
    
    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 computation fails
  - 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
  - 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 this class.
    
    Parameters:
    
    argv - the options

Class RandomForest

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.Classifier

Methods inherited from class java.lang.Object

Constructor Detail

RandomForest

Method Detail

globalInfo

getTechnicalInformation

numTreesTipText

getNumTrees

setNumTrees

numFeaturesTipText

getNumFeatures

setNumFeatures

seedTipText

setSeed

getSeed

maxDepthTipText

getMaxDepth

setMaxDepth

measureOutOfBagError

enumerateMeasures

getMeasure

listOptions

getOptions

setOptions

getCapabilities

buildClassifier

distributionForInstance

toString

getRevision

main