milk.classifiers
Class MIWrapper

java.lang.Object
  |
  +--milk.classifiers.MIClassifier
        |
        +--milk.classifiers.MIWrapper

All Implemented Interfaces:

java.lang.Cloneable, MITransform, weka.core.OptionHandler, java.io.Serializable

Direct Known Subclasses:

SimpleMI

public class MIWrapper

extends MIClassifier

implements weka.core.OptionHandler, MITransform

Weighted Wrapper method from Eibe Valid options are:

-D
Turn on debugging output.

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

-P method index
Set which method to use in testing: 1.arithmatic average; 2.geometric average. (default: 1)

See Also:

Serialized Form

Field Summary

protected weka.core.Instances	m_Attributes All attribute names
protected weka.classifiers.Classifier	m_Classifier
protected int	m_ClassIndex The index of the class attribute
protected boolean	m_Debug Debugging output
protected int	m_IdIndex
protected int	m_Method
protected int	m_NumClasses The number of the class labels

Constructor Summary

MIWrapper()

Method Summary

void	buildClassifier(Exemplars train) Builds the classifier
double[]	distributionForExemplar(Exemplar exmp) Computes the distribution for a given exemplar
weka.classifiers.Classifier	getClassifier() Get the classifier used as the classifier
boolean	getDebug() Gets whether debugging output will be printed.
int	getMethod() Get the method used in testing.
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
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	setClassifier(weka.classifiers.Classifier newClassifier) Set the base classifier.
void	setDebug(boolean debug) Sets whether debugging output will be printed.
void	setMethod(int newMethod) Set the method used in testing.
void	setOptions(java.lang.String[] options) Parses a given list of options.
java.lang.String	toString() Gets a string describing the classifier.
weka.core.Instances	transform(Exemplars train) transform the given exemplars to an Instances object.

Methods inherited from class milk.classifiers.MIClassifier

classifyExemplar, forName, makeCopies

Methods inherited from class java.lang.Object

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

Field Detail

m_ClassIndex

protected int m_ClassIndex

The index of the class attribute

m_NumClasses

protected int m_NumClasses

The number of the class labels

m_IdIndex

protected int m_IdIndex

m_Debug

protected boolean m_Debug

Debugging output

m_Attributes

protected weka.core.Instances m_Attributes

All attribute names

m_Classifier

protected weka.classifiers.Classifier m_Classifier

m_Method

protected int m_Method

Constructor Detail

MIWrapper

public MIWrapper()

Method Detail

listOptions

public java.util.Enumeration listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface weka.core.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.

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

-P method_index
Set which method to use in testing: 1.arithmatic average; 2.geometric average. (default: 1)

Specified by:

setOptions in interface weka.core.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 weka.core.OptionHandler

Returns:

an array of strings suitable for passing to setOptions

setDebug

public void setDebug(boolean debug)

Sets whether debugging output will be printed.

Parameters:

debug - true if debugging output should be printed

getDebug

public boolean getDebug()

Gets whether debugging output will be printed.

Returns:

true if debugging output will be printed

setClassifier

public void setClassifier(weka.classifiers.Classifier newClassifier)

Set the base classifier.

Parameters:

newClassifier - the Classifier to use.

getClassifier

public weka.classifiers.Classifier getClassifier()

Get the classifier used as the classifier

Returns:

the classifier used as the classifier

setMethod

public void setMethod(int newMethod)

Set the method used in testing.

Parameters:

newMethod - the index of method to use.

getMethod

public int getMethod()

Get the method used in testing.

Returns:

the index of method used in testing.

transform

public weka.core.Instances transform(Exemplars train)
                              throws java.lang.Exception

Description copied from interface: MITransform

transform the given exemplars to an Instances object.

Specified by:

transform in interface MITransform

Returns:

the transformed instances

Throws:

java.lang.Exception - if transformation is not successful

buildClassifier

public void buildClassifier(Exemplars train)
                     throws java.lang.Exception

Builds the classifier

Specified by:

buildClassifier in class MIClassifier

Parameters:

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

Throws:

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

distributionForExemplar

public double[] distributionForExemplar(Exemplar exmp)
                                 throws java.lang.Exception

Computes the distribution for a given exemplar

Overrides:

distributionForExemplar in class MIClassifier

Parameters:

exmp - the exemplar for which distribution is computed

Returns:

the distribution

Throws:

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

toString

public java.lang.String toString()

Gets a string describing the classifier.

Overrides:

toString in class java.lang.Object

Returns:

a string describing the classifer built.

main

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

Main method for testing this class.

Parameters:

argv - should contain the command line arguments to the scheme (see Evaluation)