Package weka.classifiers.meta
Class OrdinalClassClassifier
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.meta.OrdinalClassClassifier
- All Implemented Interfaces:
Serializable,Cloneable,CapabilitiesHandler,OptionHandler,RevisionHandler,TechnicalInformationHandler
public class OrdinalClassClassifier
extends SingleClassifierEnhancer
implements OptionHandler, TechnicalInformationHandler
Meta classifier that allows standard classification algorithms to be applied to ordinal class problems.
For more information see:
Eibe Frank, Mark Hall: A Simple Approach to Ordinal Classification. In: 12th European Conference on Machine Learning, 145-156, 2001. BibTeX:
For more information see:
Eibe Frank, Mark Hall: A Simple Approach to Ordinal Classification. In: 12th European Conference on Machine Learning, 145-156, 2001. BibTeX:
@inproceedings{Frank2001,
author = {Eibe Frank and Mark Hall},
booktitle = {12th European Conference on Machine Learning},
pages = {145-156},
publisher = {Springer},
title = {A Simple Approach to Ordinal Classification},
year = {2001}
}
Valid options are:
-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.J48)
Options specific to classifier weka.classifiers.trees.J48:
-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances per leaf. (default 2)
-R Use reduced error pruning.
-N <number of folds> Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3)
-B Use binary splits only.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
- Version:
- $Revision 1.0 $
- Author:
- Mark Hall
- See Also:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoidbuildClassifier(Instances insts) Builds the classifiers.double[]Returns the distribution for an instance.Returns default capabilities of the classifier.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 this attribute evaluatorReturns an enumeration describing the available options.static voidMain method for testing this class.voidsetOptions(String[] options) Parses a given list of options.toString()Prints the classifiers.Methods inherited from class weka.classifiers.SingleClassifierEnhancer
classifierTipText, getClassifier, setClassifierMethods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
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Constructor Details
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OrdinalClassClassifier
public OrdinalClassClassifier()Default constructor.
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Method Details
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globalInfo
Returns a string describing this attribute evaluator- Returns:
- a description of the evaluator 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:
getTechnicalInformationin interfaceTechnicalInformationHandler- Returns:
- the technical information about this class
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getCapabilities
Returns default capabilities of the classifier.- Specified by:
getCapabilitiesin interfaceCapabilitiesHandler- Overrides:
getCapabilitiesin classSingleClassifierEnhancer- Returns:
- the capabilities of this classifier
- See Also:
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buildClassifier
Builds the classifiers.- Specified by:
buildClassifierin classClassifier- Parameters:
insts- the training data.- Throws:
Exception- if a classifier can't be built
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distributionForInstance
Returns the distribution for an instance.- Overrides:
distributionForInstancein classClassifier- Parameters:
inst- the instance to compute the distribution for- Returns:
- the class distribution for the given instance
- Throws:
Exception- if the distribution can't be computed successfully
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listOptions
Returns an enumeration describing the available options.- Specified by:
listOptionsin interfaceOptionHandler- Overrides:
listOptionsin classSingleClassifierEnhancer- Returns:
- an enumeration of all the available options.
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setOptions
Parses a given list of options. Valid options are:-D If set, classifier is run in debug mode and may output additional info to the console
-W Full name of base classifier. (default: weka.classifiers.trees.J48)
Options specific to classifier weka.classifiers.trees.J48:
-U Use unpruned tree.
-C <pruning confidence> Set confidence threshold for pruning. (default 0.25)
-M <minimum number of instances> Set minimum number of instances per leaf. (default 2)
-R Use reduced error pruning.
-N <number of folds> Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3)
-B Use binary splits only.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-Q <seed> Seed for random data shuffling (default 1).
- Specified by:
setOptionsin interfaceOptionHandler- Overrides:
setOptionsin classSingleClassifierEnhancer- 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:
getOptionsin interfaceOptionHandler- Overrides:
getOptionsin classSingleClassifierEnhancer- Returns:
- an array of strings suitable for passing to setOptions
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toString
Prints the classifiers. -
getRevision
Returns the revision string.- Specified by:
getRevisionin interfaceRevisionHandler- Overrides:
getRevisionin classClassifier- Returns:
- the revision
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main
Main method for testing this class.- Parameters:
argv- the options
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