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Class weka.classifiers.meta.Bagging

java.lang.Object
    |
    +----weka.classifiers.Classifier
            |
            +----weka.classifiers.DistributionClassifier
                    |
                    +----weka.classifiers.meta.Bagging

public class Bagging

extends DistributionClassifier

implements OptionHandler, WeightedInstancesHandler, Randomizable, AdditionalMeasureProducer

Leo Breiman (1996). Bagging predictors. Machine Learning, 24(2):123-140.

Valid options are:

-W classname
Specify the full class name of a weak classifier as the basis for bagging (required).

-I num
Set the number of bagging iterations (default 10).

-S seed
Random number seed for resampling (default 1).

-P num
Size of each bag, as a percentage of the training size (default 100).

-O
Compute out of bag error.

Options after -- are passed to the designated classifier.

Version:

$Revision: 1.23 $

Author:

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

Author:

Len Trigg (len@reeltwo.com)

Author:

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

Bagging()

 

buildClassifier(Instances)

Bagging method.

distributionForInstance(Instance)

Calculates the class membership probabilities for the given test instance.

enumerateMeasures()

Returns an enumeration of the additional measure names.

getBagSizePercent()

Gets the size of each bag, as a percentage of the training set size.

getCalcOutOfBag()

Get whether the out of bag error is calculated.

getClassifier()

Get the classifier used as the classifier

getMeasure(String)

Returns the value of the named measure.

getNumIterations()

Gets the number of bagging iterations

getOptions()

Gets the current settings of the Classifier.

getSeed()

Gets the seed for the random number generations

listOptions()

Returns an enumeration describing the available options.

main(String[])

Main method for testing this class.

measureOutOfBagError()

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

setBagSizePercent(int)

Sets the size of each bag, as a percentage of the training set size.

setCalcOutOfBag(boolean)

Set whether the out of bag error is calculated.

setClassifier(Classifier)

Set the classifier for bagging.

setNumIterations(int)

Sets the number of bagging iterations

setOptions(String[])

Parses a given list of options.

setSeed(int)

Set the seed for random number generation.

toString()

Returns description of the bagged classifier.

public Bagging()

public java.util.Enumeration listOptions()

          Returns an enumeration describing the available options.

Returns:

an enumeration of all the available options.

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

          Parses a given list of options. Valid options are:

-W classname
Specify the full class name of a weak classifier as the basis for bagging (required).

-I num
Set the number of bagging iterations (default 10).

-S seed
Random number seed for resampling (default 1).

-P num
Size of each bag, as a percentage of the training size (default 100).

-O
Compute out of bag error.

Options after -- are passed to the designated classifier.

Parameters:

options - the list of options as an array of strings

Throws:

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

public java.lang.String[] getOptions()

          Gets the current settings of the Classifier.

Returns:

an array of strings suitable for passing to setOptions

public void setClassifier(Classifier newClassifier)

          Set the classifier for bagging.

Parameters:

newClassifier - the Classifier to use.

public Classifier getClassifier()

          Get the classifier used as the classifier

Returns:

the classifier used as the classifier

public int getBagSizePercent()

          Gets the size of each bag, as a percentage of the training set size.

Returns:

the bag size, as a percentage.

public void setBagSizePercent(int newBagSizePercent)

          Sets the size of each bag, as a percentage of the training set size.

Parameters:

newBagSizePercent - the bag size, as a percentage.

public void setNumIterations(int numIterations)

          Sets the number of bagging iterations

public int getNumIterations()

          Gets the number of bagging iterations

Returns:

the maximum number of bagging iterations

public void setSeed(int seed)

          Set the seed for random number generation.

Parameters:

seed - the seed

public int getSeed()

          Gets the seed for the random number generations

Returns:

the seed for the random number generation

public void setCalcOutOfBag(boolean calcOutOfBag)

          Set whether the out of bag error is calculated.

Parameters:

calcOutOfBag - whether to calculate the out of bag error

public boolean getCalcOutOfBag()

          Get whether the out of bag error is calculated.

Returns:

whether the out of bag error is calculated

public double measureOutOfBagError()

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

Returns:

the out of bag error

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

          Bagging method.

Parameters:

data - the training data to be used for generating the bagged classifier.

Throws:

java.lang.Exception - if the classifier could not be built successfully

Overrides:

buildClassifier in class Classifier

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

          Calculates the class membership probabilities for the given test instance.

Parameters:

instance - the instance to be classified

Returns:

preedicted class probability distribution

Throws:

java.lang.Exception - if distribution can't be computed successfully

Overrides:

distributionForInstance in class DistributionClassifier

public java.lang.String toString()

          Returns description of the bagged classifier.

Returns:

description of the bagged classifier as a string

Overrides:

toString in class java.lang.Object

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

          Main method for testing this class.

Parameters:

argv - the options

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