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java.lang.Objectweka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.RandomizableSingleClassifierEnhancer
weka.classifiers.meta.nestedDichotomies.ClassBalancedND
public class ClassBalancedND
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random class-balanced tree structure.
For more info, check
Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems. In: PKDD, 84-95, 2005.
Eibe Frank, Stefan Kramer: Ensembles of nested dichotomies for multi-class problems. In: Twenty-first International Conference on Machine Learning, 2004.
@inproceedings{Dong2005, author = {Lin Dong and Eibe Frank and Stefan Kramer}, booktitle = {PKDD}, pages = {84-95}, publisher = {Springer}, title = {Ensembles of Balanced Nested Dichotomies for Multi-class Problems}, year = {2005} } @inproceedings{Frank2004, author = {Eibe Frank and Stefan Kramer}, booktitle = {Twenty-first International Conference on Machine Learning}, publisher = {ACM}, title = {Ensembles of nested dichotomies for multi-class problems}, year = {2004} }Valid options are:
-S <num> Random number seed. (default 1)
-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).
Constructor Summary | |
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ClassBalancedND()
Constructor. |
Method Summary | |
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void |
buildClassifier(Instances data)
Builds tree recursively. |
double[] |
distributionForInstance(Instance inst)
Predicts the class distribution for a given instance |
Capabilities |
getCapabilities()
Returns default capabilities of the classifier. |
java.lang.String |
getRevision()
Returns the revision string. |
java.lang.String |
getString(int[] indices)
Returns the list of indices as a 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()
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static void |
main(java.lang.String[] argv)
Main method for testing this class. |
void |
setHashtable(java.util.Hashtable table)
Set hashtable from END. |
java.lang.String |
toString()
Outputs the classifier as a string. |
Methods inherited from class weka.classifiers.RandomizableSingleClassifierEnhancer |
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getOptions, getSeed, listOptions, seedTipText, setOptions, setSeed |
Methods inherited from class weka.classifiers.SingleClassifierEnhancer |
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classifierTipText, getClassifier, setClassifier |
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 |
Constructor Detail |
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public ClassBalancedND()
Method Detail |
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public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
public void setHashtable(java.util.Hashtable table)
table
- the hashtable to usepublic Capabilities getCapabilities()
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class SingleClassifierEnhancer
Capabilities
public void buildClassifier(Instances data) throws java.lang.Exception
buildClassifier
in class Classifier
data
- contains the (multi-class) instances
java.lang.Exception
- if the building failspublic double[] distributionForInstance(Instance inst) throws java.lang.Exception
distributionForInstance
in class Classifier
inst
- the (multi-class) instance to be classified
java.lang.Exception
- if computing failspublic java.lang.String getString(int[] indices)
indices
- the indices to return as string
public java.lang.String globalInfo()
public java.lang.String toString()
toString
in class java.lang.Object
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class Classifier
public static void main(java.lang.String[] argv)
argv
- the options
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