weka.classifiers.functions.supportVector

Class RegSMOImproved

java.lang.Object

weka.classifiers.functions.supportVector.RegOptimizer

weka.classifiers.functions.supportVector.RegSMO

weka.classifiers.functions.supportVector.RegSMOImproved

All Implemented Interfaces:

java.io.Serializable, OptionHandler, RevisionHandler, TechnicalInformationHandler

public class RegSMOImproved
extends RegSMO
implements TechnicalInformationHandler

Learn SVM for regression using SMO with Shevade, Keerthi, et al. adaption of the stopping criterion.

For more information see:

S.K. Shevade, S.S. Keerthi, C. Bhattacharyya, K.R.K. Murthy: Improvements to the SMO Algorithm for SVM Regression. In: IEEE Transactions on Neural Networks, 1999.

S.K. Shevade, S.S. Keerthi, C. Bhattacharyya, K.R.K. Murthy (1999). Improvements to the SMO Algorithm for SVM Regression. Control Division, Dept. of Mechanical Engineering.

BibTeX:

 @inproceedings{Shevade1999,
    author = {S.K. Shevade and S.S. Keerthi and C. Bhattacharyya and K.R.K. Murthy},
    booktitle = {IEEE Transactions on Neural Networks},
    title = {Improvements to the SMO Algorithm for SVM Regression},
    year = {1999},
    PS = {http://guppy.mpe.nus.edu.sg/\~mpessk/svm/ieee_smo_reg.ps.gz}
 }
 
 @techreport{Shevade1999,
    address = {Control Division, Dept. of Mechanical Engineering},
    author = {S.K. Shevade and S.S. Keerthi and C. Bhattacharyya and K.R.K. Murthy},
    institution = {National University of Singapore},
    number = {CD-99-16},
    title = {Improvements to the SMO Algorithm for SVM Regression},
    year = {1999},
    PS = {http://guppy.mpe.nus.edu.sg/\~mpessk/svm/smoreg_mod.ps.gz}
 }
 

Valid options are:

 -T <double>
  The tolerance parameter for checking the stopping criterion.
  (default 0.001)
 

 -V
  Use variant 1 of the algorithm when true, otherwise use variant 2.
  (default true)
 

 -P <double>
  The epsilon for round-off error.
  (default 1.0e-12)
 

 -L <double>
  The epsilon parameter in epsilon-insensitive loss function.
  (default 1.0e-3)
 

 -W <double>
  The random number seed.
  (default 1)
 

Version:

$Revision: 10169 $

Author:

Remco Bouckaert (remco@cs.waikato.ac.nz,rrb@xm.co.nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static int	I0
static int	I0a
static int	I0b
static int	I1
static int	I2
static int	I3

Fields inherited from class weka.classifiers.functions.supportVector.RegOptimizer

m_alpha, m_alphaStar

Constructor Summary

Constructors

Constructor and Description
RegSMOImproved()

Method Summary

Modifier and Type	Method and Description
void	buildClassifier(Instances instances) learn SVM parameters from data using Keerthi's SMO algorithm.
java.lang.String[]	getOptions() Gets the current settings of the object.
java.lang.String	getRevision() Returns the revision string.
TechnicalInformation	getTechnicalInformation() Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
double	getTolerance() returns the current tolerance
java.lang.String	globalInfo() Returns a string describing the object
boolean	isUseVariant1() Whether variant 1 is used
java.util.Enumeration<Option>	listOptions() Returns an enumeration describing the available options
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setTolerance(double d) sets the tolerance
void	setUseVariant1(boolean b) Sets whether to use variant 1
java.lang.String	toleranceTipText() Returns the tip text for this property
java.lang.String	useVariant1TipText() Returns the tip text for this property

Methods inherited from class weka.classifiers.functions.supportVector.RegSMO

epsilonTipText, getEpsilon, optimize, setEpsilon

Methods inherited from class weka.classifiers.functions.supportVector.RegOptimizer

epsilonParameterTipText, getCacheHits, getEpsilonParameter, getKernelEvaluations, getSeed, modelBuilt, seedTipText, setEpsilonParameter, setSeed, setSMOReg, SVMOutput, toString

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.OptionHandler

makeCopy

Field Detail

I0

public static final int I0

See Also:

Constant Field Values

I0a

public static final int I0a

See Also:

Constant Field Values

I0b

public static final int I0b

See Also:

Constant Field Values

I1

public static final int I1

See Also:

Constant Field Values

I2

public static final int I2

See Also:

Constant Field Values

I3

public static final int I3

See Also:

Constant Field Values

Constructor Detail

RegSMOImproved

public RegSMOImproved()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing the object

Overrides:

globalInfo in class RegSMO

Returns:

a description suitable for displaying in the explorer/experimenter gui

getTechnicalInformation

public TechnicalInformation getTechnicalInformation()

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

Specified by:

getTechnicalInformation in interface TechnicalInformationHandler

Overrides:

getTechnicalInformation in class RegSMO

Returns:

the technical information about this class

listOptions

public java.util.Enumeration<Option> listOptions()

Returns an enumeration describing the available options

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class RegSMO

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:

 -T <double>
  The tolerance parameter for checking the stopping criterion.
  (default 0.001)
 

 -V
  Use variant 1 of the algorithm when true, otherwise use variant 2.
  (default true)
 

 -P <double>
  The epsilon for round-off error.
  (default 1.0e-12)
 

 -L <double>
  The epsilon parameter in epsilon-insensitive loss function.
  (default 1.0e-3)
 

 -W <double>
  The random number seed.
  (default 1)
 

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class RegSMO

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 object.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class RegSMO

Returns:

an array of strings suitable for passing to setOptions

toleranceTipText

public java.lang.String toleranceTipText()

Returns the tip text for this property

Returns:

a description suitable for displaying in the explorer/experimenter gui

getTolerance

public double getTolerance()

returns the current tolerance

Returns:

the tolerance

setTolerance

public void setTolerance(double d)

sets the tolerance

Parameters:

d - the new tolerance

useVariant1TipText

public java.lang.String useVariant1TipText()

Returns the tip text for this property

Returns:

a description suitable for displaying in the explorer/experimenter gui

isUseVariant1

public boolean isUseVariant1()

Whether variant 1 is used

Returns:

true if variant 1 is used

setUseVariant1

public void setUseVariant1(boolean b)

Sets whether to use variant 1

Parameters:

b - if true then variant 1 is used

buildClassifier

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

learn SVM parameters from data using Keerthi's SMO algorithm. Subclasses should implement something more interesting.

Overrides:

buildClassifier in class RegSMO

Parameters:

instances - the data to work with

Throws:

java.lang.Exception - if something goes wrong

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class RegSMO

Returns:

the revision