Package weka.classifiers.functions

Class PLSWeighted

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.functions.PLSWeighted

All Implemented Interfaces:

Serializable, Cloneable, weka.classifiers.Classifier, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, GenericPLSMatrixAccess, weka.core.OptionHandler, weka.core.RevisionHandler, weka.core.WeightedInstancesHandler

public class PLSWeighted
extends weka.classifiers.AbstractClassifier
implements weka.core.WeightedInstancesHandler, GenericPLSMatrixAccess

A wrapper classifier for the PLS filter, utilizing the filter's ability to perform predictions.

Valid options are:

 -algorithm <algorithm specification>
  The PLS algorithm to use. Full classname of filter to include,  followed by scheme options.
  (default: weka.filters.supervised.attribute.pls.PLS1)

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

 -do-not-check-capabilities
  If set, classifier capabilities are not checked before classifier is built
  (use with caution).

 -num-decimal-places
  The number of decimal places for the output of numbers in the model (default 2).

 
 Options specific to algorithm weka.filters.supervised.attribute.pls.PLS1 ('-algorithm'):
 

 -debug <value>
  If enabled, additional info may be output to the console.
  (default: false)

 -preprocessing <value>
  The type of preprocessing to perform.
  (default: CENTER)

 -C <value>
  The number of components to compute.
  (default: 20)

 -prediction <value>
  The type of prediction to perform.
  (default: NONE)

Version:

$Revision$

Author:

fracpete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected AbstractPLS	m_Algorithm	the PLS algorithm
protected PLS	m_Filter	the actual filter to use

Fields inherited from class weka.classifiers.AbstractClassifier

BATCH_SIZE_DEFAULT, m_BatchSize, m_Debug, m_DoNotCheckCapabilities, m_numDecimalPlaces, NUM_DECIMAL_PLACES_DEFAULT

Constructor Summary

Constructors

Constructor	Description
PLSWeighted()

Method Summary

Modifier and Type	Method	Description
String	algorithmTipText()	Returns the tip text for this property
void	buildClassifier(weka.core.Instances data)	builds the classifier
double	classifyInstance(weka.core.Instance instance)	Classifies the given test instance.
AbstractPLS	getAlgorithm()	Get the PLS algorithm.
weka.core.Capabilities	getCapabilities()	Returns default capabilities of the classifier.
AbstractPLS	getDefaultAlgorithm()	Returns the default PLS filter.
weka.core.matrix.Matrix	getLoadings()	Returns the loadings, if available.
weka.core.matrix.Matrix	getMatrix(String name)	Returns the matrix with the specified name.
String[]	getMatrixNames()	Returns the all the available matrices.
String[]	getOptions()	returns the options of the current setup
String	getRevision()	Returns the revision string.
String	globalInfo()	Returns a string describing classifier
boolean	hasLoadings()	Whether the algorithm supports return of loadings.
Enumeration	listOptions()	Gets an enumeration describing the available options.
static void	main(String[] args)	Main method for running this classifier from commandline.
void	setAlgorithm(AbstractPLS value)	Set the PLS algorithm (only used for setup).
void	setOptions(String[] options)	Parses the options for this object.
String	toString()	returns a string representation of the classifier

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, debugTipText, distributionForInstance, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

Methods inherited from class java.lang.Object

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

Field Detail

m_Algorithm

protected AbstractPLS m_Algorithm

the PLS algorithm

m_Filter

protected PLS m_Filter

the actual filter to use

Constructor Detail

PLSWeighted

public PLSWeighted()

Method Detail

globalInfo

public String globalInfo()

Returns a string describing classifier

Returns:

a description suitable for displaying in the explorer/experimenter gui

listOptions

public Enumeration listOptions()

Gets an enumeration describing the available options.

Specified by:

listOptions in interface weka.core.OptionHandler

Overrides:

listOptions in class weka.classifiers.AbstractClassifier

Returns:

an enumeration of all the available options.

getOptions

public String[] getOptions()

returns the options of the current setup

Specified by:

getOptions in interface weka.core.OptionHandler

Overrides:

getOptions in class weka.classifiers.AbstractClassifier

Returns:

the current options

setOptions

public void setOptions(String[] options)
                throws Exception

Parses the options for this object.

Specified by:

setOptions in interface weka.core.OptionHandler

Overrides:

setOptions in class weka.classifiers.AbstractClassifier

Parameters:

options - the options to use

Throws:

Exception - if setting of options fails

getDefaultAlgorithm

public AbstractPLS getDefaultAlgorithm()

Returns the default PLS filter.

Returns:

the default filter

setAlgorithm

public void setAlgorithm(AbstractPLS value)

Set the PLS algorithm (only used for setup).

Parameters:

value - the algorithm

getAlgorithm

public AbstractPLS getAlgorithm()

Get the PLS algorithm.

Returns:

the PLS algorithm

algorithmTipText

public String algorithmTipText()

Returns the tip text for this property

Returns:

tip text for this property suitable for displaying in the explorer/experimenter gui

getCapabilities

public weka.core.Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Specified by:

getCapabilities in interface weka.classifiers.Classifier

Overrides:

getCapabilities in class weka.classifiers.AbstractClassifier

Returns:

the capabilities of this classifier

buildClassifier

public void buildClassifier(weka.core.Instances data)
                     throws Exception

builds the classifier

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Parameters:

data - the training instances

Throws:

Exception - if something goes wrong

classifyInstance

public double classifyInstance(weka.core.Instance instance)
                        throws Exception

Classifies the given test instance. The instance has to belong to a dataset when it's being classified.

Specified by:

classifyInstance in interface weka.classifiers.Classifier

Overrides:

classifyInstance in class weka.classifiers.AbstractClassifier

Parameters:

instance - the instance to be classified

Returns:

the predicted most likely class for the instance or Instance.missingValue() if no prediction is made

Throws:

Exception - if an error occurred during the prediction

getMatrixNames

public String[] getMatrixNames()

Returns the all the available matrices.

Specified by:

getMatrixNames in interface GenericPLSMatrixAccess

Returns:

the names of the matrices

getMatrix

public weka.core.matrix.Matrix getMatrix(String name)

Returns the matrix with the specified name.

Specified by:

getMatrix in interface GenericPLSMatrixAccess

Parameters:

name - the name of the matrix

Returns:

the matrix, null if not available

hasLoadings

public boolean hasLoadings()

Whether the algorithm supports return of loadings.

Specified by:

hasLoadings in interface GenericPLSMatrixAccess

Returns:

true if supported

See Also:

getLoadings()

getLoadings

public weka.core.matrix.Matrix getLoadings()

Returns the loadings, if available.

Specified by:

getLoadings in interface GenericPLSMatrixAccess

Returns:

the loadings, null if not available

toString

public String toString()

returns a string representation of the classifier

Overrides:

toString in class Object

Returns:

a string representation of the classifier

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface weka.core.RevisionHandler

Overrides:

getRevision in class weka.classifiers.AbstractClassifier

Returns:

the revision

main

public static void main(String[] args)

Main method for running this classifier from commandline.

Parameters:

args - the options