Class RegSMO
java.lang.Object
weka.classifiers.functions.supportVector.RegOptimizer
weka.classifiers.functions.supportVector.RegSMO
- All Implemented Interfaces:
Serializable
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
- Direct Known Subclasses:
RegSMOImproved
Implementation of SMO for support vector regression
as described in :
A.J. Smola, B. Schoelkopf (1998). A tutorial on support vector regression. BibTeX:
A.J. Smola, B. Schoelkopf (1998). A tutorial on support vector regression. BibTeX:
@misc{Smola1998, author = {A.J. Smola and B. Schoelkopf}, note = {NeuroCOLT2 Technical Report NC2-TR-1998-030}, title = {A tutorial on support vector regression}, year = {1998} }Valid options are:
-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:
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Field Summary
Fields inherited from class weka.classifiers.functions.supportVector.RegOptimizer
m_alpha, m_alphaStar
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptionvoid
buildClassifier
(Instances instances) learn SVM parameters from data using Smola's SMO algorithm.Returns the tip text for this propertydouble
Get the value of epsilon.String[]
Gets the current settings of the classifier.Returns the revision string.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.Returns a string describing classifierReturns an enumeration describing the available optionsvoid
optimize()
finds alpha and alpha* parameters that optimize the SVM target functionvoid
setEpsilon
(double v) Set the value of epsilon.void
setOptions
(String[] options) Parses a given list of options.Methods inherited from class weka.classifiers.functions.supportVector.RegOptimizer
epsilonParameterTipText, getCacheHits, getEpsilonParameter, getKernelEvaluations, getSeed, modelBuilt, seedTipText, setEpsilonParameter, setSeed, setSMOReg, SVMOutput, toString
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Constructor Details
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RegSMO
public RegSMO()default constructor
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Method Details
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globalInfo
Returns a string describing classifier- Returns:
- a description suitable for displaying in the explorer/experimenter gui
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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 interfaceTechnicalInformationHandler
- Returns:
- the technical information about this class
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listOptions
Returns an enumeration describing the available options- Specified by:
listOptions
in interfaceOptionHandler
- Overrides:
listOptions
in classRegOptimizer
- Returns:
- an enumeration of all the available options
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setOptions
Parses a given list of options. Valid options are:-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 interfaceOptionHandler
- Overrides:
setOptions
in classRegOptimizer
- Parameters:
options
- the list of options as an array of strings- Throws:
Exception
- if an option is not supported
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getOptions
Gets the current settings of the classifier.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classRegOptimizer
- Returns:
- an array of strings suitable for passing to setOptions
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epsilonTipText
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getEpsilon
public double getEpsilon()Get the value of epsilon.- Returns:
- Value of epsilon.
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setEpsilon
public void setEpsilon(double v) Set the value of epsilon.- Parameters:
v
- Value to assign to epsilon.
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optimize
finds alpha and alpha* parameters that optimize the SVM target function- Throws:
Exception
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buildClassifier
learn SVM parameters from data using Smola's SMO algorithm. Subclasses should implement something more interesting.- Overrides:
buildClassifier
in classRegOptimizer
- Parameters:
instances
- the data to learn from- Throws:
Exception
- if something goes wrong
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getRevision
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classRegOptimizer
- Returns:
- the revision
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