Package weka.classifiers.trees
Class DecisionStump
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.trees.DecisionStump
- All Implemented Interfaces:
Serializable,Cloneable,Sourcable,CapabilitiesHandler,OptionHandler,RevisionHandler,WeightedInstancesHandler
Class for building and using a decision stump. Usually used in conjunction with a boosting algorithm. Does regression (based on mean-squared error) or classification (based on entropy). Missing is treated as a separate value.
Typical usage:
java weka.classifiers.meta.LogitBoost -I 100 -W weka.classifiers.trees.DecisionStump
-t training_data
Valid options are:
-D If set, classifier is run in debug mode and may output additional info to the console
- Version:
- $Revision: 5535 $
- Author:
- Eibe Frank (eibe@cs.waikato.ac.nz)
- See Also:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoidbuildClassifier(Instances instances) Generates the classifier.double[]distributionForInstance(Instance instance) Calculates the class membership probabilities for the given test instance.Returns default capabilities of the classifier.Returns the revision string.Returns a string describing classifierstatic voidMain method for testing this class.Returns the decision tree as Java source code.toString()Returns a description of the classifier.Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions
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Constructor Details
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DecisionStump
public DecisionStump()
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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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getCapabilities
Returns default capabilities of the classifier.- Specified by:
getCapabilitiesin interfaceCapabilitiesHandler- Overrides:
getCapabilitiesin classClassifier- Returns:
- the capabilities of this classifier
- See Also:
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buildClassifier
Generates the classifier.- Specified by:
buildClassifierin classClassifier- Parameters:
instances- set of instances serving as training data- Throws:
Exception- if the classifier has not been generated successfully
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distributionForInstance
Calculates the class membership probabilities for the given test instance.- Overrides:
distributionForInstancein classClassifier- Parameters:
instance- the instance to be classified- Returns:
- predicted class probability distribution
- Throws:
Exception- if distribution can't be computed
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toSource
Returns the decision tree as Java source code. -
toString
Returns a description of the classifier. -
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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