weka.classifiers
Class MultiScheme

java.lang.Object
  |
  +--weka.classifiers.Classifier
        |
        +--weka.classifiers.MultiScheme

All Implemented Interfaces:

java.lang.Cloneable, OptionHandler, java.io.Serializable

public class MultiScheme

extends Classifier

implements OptionHandler

Class for selecting a classifier from among several using cross validation on the training data.

Valid options from the command line are:

-D
Turn on debugging output.

-S seed
Random number seed (default 1).

-B classifierstring
Classifierstring should contain the full class name of a scheme included for selection followed by options to the classifier (required, option should be used once for each classifier).

-X num_folds
Use cross validation error as the basis for classifier selection. (default 0, is to use error on the training data instead)

Author:

Len Trigg (trigg@cs.waikato.ac.nz)

See Also:

Serialized Form

Field Summary

protected Classifier	m_Classifier The classifier that had the best performance on training data.
protected int	m_ClassifierIndex The index into the vector for the selected scheme
protected Classifier[]	m_Classifiers The list of classifiers
protected boolean	m_Debug Debugging mode, gives extra output if true
protected int	m_NumXValFolds Number of folds to use for cross validation (0 means use training error for selection)
protected int	m_Seed Random number seed

Constructor Summary

MultiScheme()

Method Summary

void	buildClassifier(Instances data) Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
double	classifyInstance(Instance instance) Classifies a given instance using the selected classifier.
Classifier	getClassifier(int index) Gets a single classifier from the set of available classifiers.
Classifier[]	getClassifiers() Gets the list of possible classifers to choose from.
protected java.lang.String	getClassifierSpec(int index) Gets the classifier specification string, which contains the class name of the classifier and any options to the classifier
boolean	getDebug() Get whether debugging is turned on
int	getNumFolds() Gets the number of folds for cross-validation.
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
int	getSeed() Gets the random number seed.
java.util.Enumeration	listOptions() Returns an enumeration describing the available options
static void	main(java.lang.String[] argv) Main method for testing this class.
void	setClassifiers(Classifier[] classifiers) Sets the list of possible classifers to choose from.
void	setDebug(boolean debug) Set debugging mode
void	setNumFolds(int numFolds) Sets the number of folds for cross-validation.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setSeed(int seed) Sets the seed for random number generation.
java.lang.String	toString() Output a representation of this classifier

Methods inherited from class weka.classifiers.Classifier

forName, makeCopies

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

m_Classifier

protected Classifier m_Classifier

The classifier that had the best performance on training data.

m_Classifiers

protected Classifier[] m_Classifiers

The list of classifiers

m_ClassifierIndex

protected int m_ClassifierIndex

The index into the vector for the selected scheme

m_NumXValFolds

protected int m_NumXValFolds

Number of folds to use for cross validation (0 means use training error for selection)

m_Debug

protected boolean m_Debug

Debugging mode, gives extra output if true

m_Seed

protected int m_Seed

Random number seed

Constructor Detail

MultiScheme

public MultiScheme()

Method Detail

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options

Specified by:

listOptions in interface OptionHandler

Returns:

an enumeration of all the available options

setOptions

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

Parses a given list of options. Valid options are:

-D
Turn on debugging output.

-S seed
Random number seed (default 1).

-B classifierstring
Classifierstring should contain the full class name of a scheme included for selection followed by options to the classifier (required, option should be used once for each classifier).

-X num_folds
Use cross validation error as the basis for classifier selection. (default 0, is to use error on the training data instead)

Specified by:

setOptions in interface OptionHandler

Parameters:

options - the list of options as an array of strings

Throws:

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

getOptions

public java.lang.String[] getOptions()

Gets the current settings of the Classifier.

Specified by:

getOptions in interface OptionHandler

Returns:

an array of strings suitable for passing to setOptions

setClassifiers

public void setClassifiers(Classifier[] classifiers)

Sets the list of possible classifers to choose from.

Parameters:

classifiers - an array of classifiers with all options set.

getClassifiers

public Classifier[] getClassifiers()

Gets the list of possible classifers to choose from.

Returns:

the array of Classifiers

getClassifier

public Classifier getClassifier(int index)

Gets a single classifier from the set of available classifiers.

Parameters:

index - the index of the classifier wanted

Returns:

the Classifier

getClassifierSpec

protected java.lang.String getClassifierSpec(int index)

Gets the classifier specification string, which contains the class name of the classifier and any options to the classifier

Parameters:

index - the index of the classifier string to retrieve, starting from 0.

Returns:

the classifier string, or the empty string if no classifier has been assigned (or the index given is out of range).

setSeed

public void setSeed(int seed)

Sets the seed for random number generation.

Parameters:

seed - the random number seed

getSeed

public int getSeed()

Gets the random number seed.

Returns:

the random number seed

getNumFolds

public int getNumFolds()

Gets the number of folds for cross-validation. A number less than 2 specifies using training error rather than cross-validation.

Returns:

the number of folds for cross-validation

setNumFolds

public void setNumFolds(int numFolds)

Sets the number of folds for cross-validation. A number less than 2 specifies using training error rather than cross-validation.

Parameters:

numFolds - the number of folds for cross-validation

setDebug

public void setDebug(boolean debug)

Set debugging mode

Parameters:

debug - true if debug output should be printed

getDebug

public boolean getDebug()

Get whether debugging is turned on

Returns:

true if debugging output is on

buildClassifier

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

Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.

Overrides:

buildClassifier in class Classifier

Parameters:

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

Throws:

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

classifyInstance

public double classifyInstance(Instance instance)
                        throws java.lang.Exception

Classifies a given instance using the selected classifier.

Overrides:

classifyInstance in class Classifier

Parameters:

instance - the instance to be classified

Throws:

java.lang.Exception - if instance could not be classified successfully

toString

public java.lang.String toString()

Output a representation of this classifier

Overrides:

toString in class java.lang.Object

main

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

Main method for testing this class.

Parameters:

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