类 MIBoost
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.mi.MIBoost
- 所有已实现的接口:
Serializable
,Cloneable
,CapabilitiesHandler
,MultiInstanceCapabilitiesHandler
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
public class MIBoost
extends SingleClassifierEnhancer
implements OptionHandler, MultiInstanceCapabilitiesHandler, TechnicalInformationHandler
MI AdaBoost method, considers the geometric mean of posterior of instances inside a bag (arithmatic mean of log-posterior) and the expectation for a bag is taken inside the loss function.
For more information about Adaboost, see:
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996. BibTeX:
For more information about Adaboost, see:
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996. BibTeX:
@inproceedings{Freund1996, address = {San Francisco}, author = {Yoav Freund and Robert E. Schapire}, booktitle = {Thirteenth International Conference on Machine Learning}, pages = {148-156}, publisher = {Morgan Kaufmann}, title = {Experiments with a new boosting algorithm}, year = {1996} }Valid options are:
-D Turn on debugging output.
-B <num> The number of bins in discretization (default 0, no discretization)
-R <num> Maximum number of boost iterations. (default 10)
-W <class name> Full name of classifier to boost. eg: weka.classifiers.bayes.NaiveBayes
-D If set, classifier is run in debug mode and may output additional info to the console
- 版本:
- $Revision: 9144 $
- 作者:
- Eibe Frank (eibe@cs.waikato.ac.nz), Xin Xu (xx5@cs.waikato.ac.nz)
- 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 exps) Builds the classifierReturns the tip text for this propertydouble[]
Computes the distribution for a given exemplarReturns default capabilities of the classifier.int
Get the number of bins in discretizationint
Get the maximum number of boost iterationsReturns the capabilities of this multi-instance classifier for the relational data.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 this filterReturns an enumeration describing the available optionsstatic void
Main method for testing this class.Returns the tip text for this propertyvoid
setDiscretizeBin
(int bin) Set the number of bins in discretizationvoid
setMaxIterations
(int maxIterations) Set the maximum number of boost iterationsvoid
setOptions
(String[] options) Parses a given list of options.toString()
Gets a string describing the classifier.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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MIBoost
public MIBoost()
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方法详细资料
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globalInfo
Returns a string describing this filter- 返回:
- a description of the filter 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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listOptions
Returns an enumeration describing the available options- 指定者:
listOptions
在接口中OptionHandler
- 覆盖:
listOptions
在类中SingleClassifierEnhancer
- 返回:
- an enumeration of all the available options
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setOptions
Parses a given list of options. Valid options are:-D Turn on debugging output.
-B <num> The number of bins in discretization (default 0, no discretization)
-R <num> Maximum number of boost iterations. (default 10)
-W <class name> Full name of classifier to boost. eg: weka.classifiers.bayes.NaiveBayes
-D If set, classifier is run in debug mode and may output additional info to the console
- 指定者:
setOptions
在接口中OptionHandler
- 覆盖:
setOptions
在类中SingleClassifierEnhancer
- 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SingleClassifierEnhancer
- 返回:
- an array of strings suitable for passing to setOptions
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maxIterationsTipText
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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setMaxIterations
public void setMaxIterations(int maxIterations) Set the maximum number of boost iterations- 参数:
maxIterations
- the maximum number of boost iterations
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getMaxIterations
public int getMaxIterations()Get the maximum number of boost iterations- 返回:
- the maximum number of boost iterations
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discretizeBinTipText
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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setDiscretizeBin
public void setDiscretizeBin(int bin) Set the number of bins in discretization- 参数:
bin
- the number of bins in discretization
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getDiscretizeBin
public int getDiscretizeBin()Get the number of bins in discretization- 返回:
- the number of bins in discretization
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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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getMultiInstanceCapabilities
Returns the capabilities of this multi-instance classifier for the relational data.- 指定者:
getMultiInstanceCapabilities
在接口中MultiInstanceCapabilitiesHandler
- 返回:
- the capabilities of this object
- 另请参阅:
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buildClassifier
Builds the classifier- 指定者:
buildClassifier
在类中Classifier
- 参数:
exps
- the training data to be used for generating the boosted classifier.- 抛出:
Exception
- if the classifier could not be built successfully
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distributionForInstance
Computes the distribution for a given exemplar- 覆盖:
distributionForInstance
在类中Classifier
- 参数:
exmp
- the exemplar for which distribution is computed- 返回:
- the classification
- 抛出:
Exception
- if the distribution can't be computed successfully
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toString
Gets a string describing the 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
- should contain the command line arguments to the scheme (see Evaluation)
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