java.lang.Object
weka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.RandomizableSingleClassifierEnhancer
weka.classifiers.meta.nestedDichotomies.ND
- 所有已实现的接口:
Serializable
,Cloneable
,CapabilitiesHandler
,OptionHandler
,Randomizable
,RevisionHandler
,TechnicalInformationHandler
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random 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. BibTeX:
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. BibTeX:
@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).
- 作者:
- Eibe Frank, Lin Dong
- 另请参阅:
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构造器概要
构造器 -
方法概要
修饰符和类型方法说明void
buildClassifier
(Instances data) Builds the classifier.void
buildClassifierForNode
(weka.classifiers.meta.nestedDichotomies.ND.NDTree node, Instances data) Builds the classifier for one node.double[]
Predicts the class distribution for a given instanceReturns default capabilities 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.static void
Main method for testing this class.void
setHashtable
(Hashtable table) Set hashtable from END.toString()
Outputs the classifier as a string.从类继承的方法 weka.classifiers.RandomizableSingleClassifierEnhancer
getOptions, getSeed, listOptions, seedTipText, setOptions, setSeed
从类继承的方法 weka.classifiers.SingleClassifierEnhancer
classifierTipText, getClassifier, setClassifier
从类继承的方法 weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
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构造器详细资料
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ND
public ND()Constructor.
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方法详细资料
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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.- 指定者:
getTechnicalInformation
在接口中TechnicalInformationHandler
- 返回:
- the technical information about this class
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setHashtable
Set hashtable from END.- 参数:
table
- the hashtable to use
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getCapabilities
Returns default capabilities of the classifier.- 指定者:
getCapabilities
在接口中CapabilitiesHandler
- 覆盖:
getCapabilities
在类中SingleClassifierEnhancer
- 返回:
- the capabilities of this classifier
- 另请参阅:
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buildClassifier
Builds the classifier.- 指定者:
buildClassifier
在类中Classifier
- 参数:
data
- the data to train the classifier with- 抛出:
Exception
- if anything goes wrong
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buildClassifierForNode
public void buildClassifierForNode(weka.classifiers.meta.nestedDichotomies.ND.NDTree node, Instances data) throws Exception Builds the classifier for one node.- 参数:
node
- the node to build the classifier fordata
- the data to work with- 抛出:
Exception
- if anything goes wrong
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distributionForInstance
Predicts the class distribution for a given instance- 覆盖:
distributionForInstance
在类中Classifier
- 参数:
inst
- the (multi-class) instance to be classified- 返回:
- the class distribution
- 抛出:
Exception
- if computing fails
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toString
Outputs the classifier as a string. -
globalInfo
- 返回:
- a description of the classifier suitable for displaying in the explorer/experimenter gui
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getRevision
Returns the revision string.- 指定者:
getRevision
在接口中RevisionHandler
- 覆盖:
getRevision
在类中Classifier
- 返回:
- the revision
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main
Main method for testing this class.- 参数:
argv
- the options
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