weka.classifiers.meta

Class RandomizableFilteredClassifier

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.SingleClassifierEnhancer

weka.classifiers.meta.FilteredClassifier

weka.classifiers.meta.RandomizableFilteredClassifier

All Implemented Interfaces:

Serializable, Cloneable, Classifier, IterativeClassifier, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, Drawable, OptionHandler, PartitionGenerator, Randomizable, RevisionHandler

public class RandomizableFilteredClassifier
extends FilteredClassifier
implements Randomizable

Class for running an arbitrary classifier on data that has been passed through an arbitrary filter. Like the classifier, the structure of the filter is based exclusively on the training data and test instances will be processed by the filter without changing their structure.

Valid options are:

 -F <filter specification>
  Full class name of filter to use, followed
  by filter options.
  eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"

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

 -W
  Full name of base classifier.
  (default: weka.classifiers.trees.J48)

 
 Options specific to classifier weka.classifiers.trees.J48:
 

 -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: 9117 $

Author:

Eibe Frank

See Also:

Serialized Form

Field Summary

Fields inherited from interface weka.core.Drawable

BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

Constructors

Constructor and Description
RandomizableFilteredClassifier() Default constructor.

Method Summary

Methods

Modifier and Type	Method and Description
void	buildClassifier(Instances data) Build the classifier on the filtered data.
String[]	getOptions() Gets the current settings of the classifier.
String	getRevision() Returns the revision string.
int	getSeed() Gets the seed for the random number generations
String	globalInfo() Returns a string describing this classifier
Enumeration<Option>	listOptions() Returns an enumeration describing the available options.
static void	main(String[] argv) Main method for testing this class.
String	seedTipText() Returns the tip text for this property
void	setOptions(String[] options) Parses a given list of options.
void	setSeed(int seed) Set the seed for random number generation.
String	toString() Output a representation of this classifier

Methods inherited from class weka.classifiers.meta.FilteredClassifier

batchSizeTipText, distributionForInstance, distributionsForInstances, done, filterTipText, generatePartition, getBatchSize, getCapabilities, getFilter, getMembershipValues, graph, graphType, initializeClassifier, next, numElements, setBatchSize, setFilter

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, getClassifier, setClassifier

Methods inherited from class weka.classifiers.AbstractClassifier

classifyInstance, debugTipText, doNotCheckCapabilitiesTipText, forName, getDebug, getDoNotCheckCapabilities, makeCopies, makeCopy, runClassifier, setDebug, setDoNotCheckCapabilities

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.classifiers.Classifier

classifyInstance

Constructor Detail

RandomizableFilteredClassifier

public RandomizableFilteredClassifier()

Default constructor.

Method Detail

globalInfo

public String globalInfo()

Returns a string describing this classifier

Overrides:

globalInfo in class FilteredClassifier

Returns:

a description of the classifier suitable for displaying in the explorer/experimenter gui

listOptions

public Enumeration<Option> listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class FilteredClassifier

Returns:

an enumeration of all the available options.

setOptions

public void setOptions(String[] options)
                throws Exception

Parses a given list of options. Valid options are:

-W classname
Specify the full class name of the base learner.

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

-S num
Set the random number seed (default 1).

Options after -- are passed to the designated classifier.

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class FilteredClassifier

Parameters:

options - the list of options as an array of strings

Throws:

Exception - if an option is not supported

getOptions

public String[] getOptions()

Gets the current settings of the classifier.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class FilteredClassifier

Returns:

an array of strings suitable for passing to setOptions

seedTipText

public 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

buildClassifier

public void buildClassifier(Instances data)
                     throws Exception

Build the classifier on the filtered data.

Specified by:

buildClassifier in interface Classifier

Overrides:

buildClassifier in class FilteredClassifier

Parameters:

data - the training data

Throws:

Exception - if the classifier could not be built successfully

toString

public String toString()

Output a representation of this classifier

Overrides:

toString in class FilteredClassifier

Returns:

a representation of this classifier

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class FilteredClassifier

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - should contain the following arguments: -t training file [-T test file] [-c class index]