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java.lang.Objectweka.classifiers.Classifier
weka.classifiers.MultipleClassifiersCombiner
weka.classifiers.RandomizableMultipleClassifiersCombiner
weka.classifiers.meta.Stacking
weka.classifiers.meta.StackingC
public class StackingC
Implements StackingC (more efficient version of stacking).
For more information, see
A.K. Seewald: How to Make Stacking Better and Faster While Also Taking Care of an Unknown Weakness. In: Nineteenth International Conference on Machine Learning, 554-561, 2002.
Note: requires meta classifier to be a numeric prediction scheme.
@inproceedings{Seewald2002, author = {A.K. Seewald}, booktitle = {Nineteenth International Conference on Machine Learning}, editor = {C. Sammut and A. Hoffmann}, pages = {554-561}, publisher = {Morgan Kaufmann Publishers}, title = {How to Make Stacking Better and Faster While Also Taking Care of an Unknown Weakness}, year = {2002} }Valid options are:
-M <scheme specification> Full name of meta classifier, followed by options. Must be a numeric prediction scheme. Default: Linear Regression.
-X <number of folds> Sets the number of cross-validation folds.
-S <num> Random number seed. (default 1)
-B <classifier specification> Full class name of classifier to include, followed by scheme options. May be specified multiple times. (default: "weka.classifiers.rules.ZeroR")
-D If set, classifier is run in debug mode and may output additional info to the console
Constructor Summary | |
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StackingC()
The constructor. |
Method Summary | |
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double[] |
distributionForInstance(Instance instance)
Classifies a given instance using the stacked classifier. |
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. |
java.lang.String |
globalInfo()
Returns a string describing classifier |
static void |
main(java.lang.String[] argv)
Main method for testing this class. |
java.lang.String |
toString()
Output a representation of this classifier |
Methods inherited from class weka.classifiers.meta.Stacking |
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buildClassifier, getCapabilities, getMetaClassifier, getNumFolds, getOptions, listOptions, metaClassifierTipText, numFoldsTipText, setMetaClassifier, setNumFolds, setOptions |
Methods inherited from class weka.classifiers.RandomizableMultipleClassifiersCombiner |
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getSeed, seedTipText, setSeed |
Methods inherited from class weka.classifiers.MultipleClassifiersCombiner |
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classifiersTipText, getClassifier, getClassifiers, setClassifiers |
Methods inherited from class weka.classifiers.Classifier |
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classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Methods inherited from interface weka.core.OptionHandler |
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getOptions, listOptions, setOptions |
Constructor Detail |
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public StackingC()
Method Detail |
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public java.lang.String globalInfo()
globalInfo
in class Stacking
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
getTechnicalInformation
in class Stacking
public double[] distributionForInstance(Instance instance) throws java.lang.Exception
distributionForInstance
in class Stacking
instance
- the instance to be classified
java.lang.Exception
- if instance could not be classified
successfullypublic java.lang.String toString()
toString
in class Stacking
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class Stacking
public static void main(java.lang.String[] argv)
argv
- should contain the following arguments:
-t training file [-T test file] [-c class index]
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