类 Decorate
- 所有已实现的接口:
Serializable
,Cloneable
,CapabilitiesHandler
,OptionHandler
,Randomizable
,RevisionHandler
,TechnicalInformationHandler
public class Decorate
extends RandomizableIteratedSingleClassifierEnhancer
implements TechnicalInformationHandler
DECORATE is a meta-learner for building diverse ensembles of classifiers by using specially constructed artificial training examples. Comprehensive experiments have demonstrated that this technique is consistently more accurate than the base classifier, Bagging and Random Forests.Decorate also obtains higher accuracy than Boosting on small training sets, and achieves comparable performance on larger training sets.
For more details see:
P. Melville, R. J. Mooney: Constructing Diverse Classifier Ensembles Using Artificial Training Examples. In: Eighteenth International Joint Conference on Artificial Intelligence, 505-510, 2003.
P. Melville, R. J. Mooney (2004). Creating Diversity in Ensembles Using Artificial Data. Information Fusion: Special Issue on Diversity in Multiclassifier Systems.. BibTeX:
For more details see:
P. Melville, R. J. Mooney: Constructing Diverse Classifier Ensembles Using Artificial Training Examples. In: Eighteenth International Joint Conference on Artificial Intelligence, 505-510, 2003.
P. Melville, R. J. Mooney (2004). Creating Diversity in Ensembles Using Artificial Data. Information Fusion: Special Issue on Diversity in Multiclassifier Systems.. BibTeX:
@inproceedings{Melville2003, author = {P. Melville and R. J. Mooney}, booktitle = {Eighteenth International Joint Conference on Artificial Intelligence}, pages = {505-510}, title = {Constructing Diverse Classifier Ensembles Using Artificial Training Examples}, year = {2003} } @article{Melville2004, author = {P. Melville and R. J. Mooney}, journal = {Information Fusion: Special Issue on Diversity in Multiclassifier Systems}, note = {submitted}, title = {Creating Diversity in Ensembles Using Artificial Data}, year = {2004} }Valid options are:
-E Desired size of ensemble. (default 15)
-R Factor that determines number of artificial examples to generate. Specified proportional to training set size. (default 1.0)
-S <num> Random number seed. (default 1)
-I <num> Number of iterations. (default 50)
-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).Options after -- are passed to the designated classifier.
- 版本:
- $Revision: 8037 $
- 作者:
- Prem Melville (melville@cs.utexas.edu)
- 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Returns the tip text for this propertyvoid
buildClassifier
(Instances data) Build Decorate classifierReturns the tip text for this propertydouble[]
distributionForInstance
(Instance instance) Calculates the class membership probabilities for the given test instance.double
Factor that determines number of artificial examples to generate.Returns default capabilities of the classifier.int
Gets the desired size of the committee.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 classifierReturns an enumeration describing the available optionsstatic void
Main method for testing this class.Returns the tip text for this propertyvoid
setArtificialSize
(double newArtSize) Sets factor that determines number of artificial examples to generate.void
setDesiredSize
(int newDesiredSize) Sets the desired size of the committee.void
setOptions
(String[] options) Parses a given list of options.toString()
Returns description of the Decorate classifier.从类继承的方法 weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
getSeed, seedTipText, setSeed
从类继承的方法 weka.classifiers.IteratedSingleClassifierEnhancer
getNumIterations, setNumIterations
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
-
Decorate
public Decorate()Constructor.
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方法详细资料
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listOptions
Returns an enumeration describing the available options- 指定者:
listOptions
在接口中OptionHandler
- 覆盖:
listOptions
在类中RandomizableIteratedSingleClassifierEnhancer
- 返回:
- an enumeration of all the available options
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setOptions
Parses a given list of options. Valid options are:-E Desired size of ensemble. (default 15)
-R Factor that determines number of artificial examples to generate. Specified proportional to training set size. (default 1.0)
-S <num> Random number seed. (default 1)
-I <num> Number of iterations. (default 50)
-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).
Options after -- are passed to the designated classifier.- 指定者:
setOptions
在接口中OptionHandler
- 覆盖:
setOptions
在类中RandomizableIteratedSingleClassifierEnhancer
- 参数:
options
- the list of options as an array of strings- 抛出:
Exception
- if an option is not supported
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getOptions
Gets the current settings of the Classifier.- 指定者:
getOptions
在接口中OptionHandler
- 覆盖:
getOptions
在类中RandomizableIteratedSingleClassifierEnhancer
- 返回:
- an array of strings suitable for passing to setOptions
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desiredSizeTipText
Returns the tip text for this property- 返回:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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numIterationsTipText
Returns the tip text for this property- 覆盖:
numIterationsTipText
在类中IteratedSingleClassifierEnhancer
- 返回:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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artificialSizeTipText
Returns the tip text for this property- 返回:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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globalInfo
Returns a string describing classifier- 返回:
- a description 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.- 指定者:
getTechnicalInformation
在接口中TechnicalInformationHandler
- 返回:
- the technical information about this class
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getArtificialSize
public double getArtificialSize()Factor that determines number of artificial examples to generate.- 返回:
- factor that determines number of artificial examples to generate
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setArtificialSize
public void setArtificialSize(double newArtSize) Sets factor that determines number of artificial examples to generate.- 参数:
newArtSize
- factor that determines number of artificial examples to generate
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getDesiredSize
public int getDesiredSize()Gets the desired size of the committee.- 返回:
- the desired size of the committee
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setDesiredSize
public void setDesiredSize(int newDesiredSize) Sets the desired size of the committee.- 参数:
newDesiredSize
- the desired size of the committee
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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
Build Decorate classifier- 覆盖:
buildClassifier
在类中IteratedSingleClassifierEnhancer
- 参数:
data
- the training data to be used for generating the classifier- 抛出:
Exception
- if the classifier could not be built successfully
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distributionForInstance
Calculates the class membership probabilities for the given test instance.- 覆盖:
distributionForInstance
在类中Classifier
- 参数:
instance
- the instance to be classified- 返回:
- predicted class probability distribution
- 抛出:
Exception
- if distribution can't be computed successfully
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toString
Returns description of the Decorate classifier. -
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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