类 MIWrapper
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.mi.MIWrapper
- 所有已实现的接口:
Serializable
,Cloneable
,CapabilitiesHandler
,MultiInstanceCapabilitiesHandler
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
public class MIWrapper
extends SingleClassifierEnhancer
implements MultiInstanceCapabilitiesHandler, OptionHandler, TechnicalInformationHandler
A simple Wrapper method for applying standard propositional learners to multi-instance data.
For more information see:
E. T. Frank, X. Xu (2003). Applying propositional learning algorithms to multi-instance data. Department of Computer Science, University of Waikato, Hamilton, NZ. BibTeX:
For more information see:
E. T. Frank, X. Xu (2003). Applying propositional learning algorithms to multi-instance data. Department of Computer Science, University of Waikato, Hamilton, NZ. BibTeX:
@techreport{Frank2003, address = {Department of Computer Science, University of Waikato, Hamilton, NZ}, author = {E. T. Frank and X. Xu}, institution = {University of Waikato}, month = {06}, title = {Applying propositional learning algorithms to multi-instance data}, year = {2003} }Valid options are:
-P [1|2|3] The method used in testing: 1.arithmetic average 2.geometric average 3.max probability of positive bag. (default: 1)
-A [0|1|2|3] The type of weight setting for each single-instance: 0.keep the weight to be the same as the original value; 1.weight = 1.0 2.weight = 1.0/Total number of single-instance in the corresponding bag 3. weight = Total number of single-instance / (Total number of bags * Total number of single-instance in the corresponding bag). (default: 3)
-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.rules.ZeroR)
Options specific to classifier weka.classifiers.rules.ZeroR:
-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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字段概要
字段修饰符和类型字段说明static final Tag[]
the test methodsstatic final int
arithmetic averagestatic final int
geometric averagestatic final int
max probability of positive bag -
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 classifierdouble[]
Computes the distribution for a given exemplarReturns default capabilities of the classifier.Get the method used in testing.Returns 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 the current weighting method for instances.Returns a string describing this filterReturns an enumeration describing the available options.static void
Main method for testing this class.Returns the tip text for this propertyvoid
setMethod
(SelectedTag method) Set the method used in testing.void
setOptions
(String[] options) Parses a given list of options.void
setWeightMethod
(SelectedTag method) The new method for weighting the instances.toString()
Gets a string describing the classifier.Returns the tip text for this property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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字段详细资料
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TESTMETHOD_ARITHMETIC
public static final int TESTMETHOD_ARITHMETICarithmetic average- 另请参阅:
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TESTMETHOD_GEOMETRIC
public static final int TESTMETHOD_GEOMETRICgeometric average- 另请参阅:
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TESTMETHOD_MAXPROB
public static final int TESTMETHOD_MAXPROBmax probability of positive bag- 另请参阅:
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TAGS_TESTMETHOD
the test methods
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构造器详细资料
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MIWrapper
public MIWrapper()
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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
-
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.
-
setOptions
Parses a given list of options. Valid options are:-P [1|2|3] The method used in testing: 1.arithmetic average 2.geometric average 3.max probability of positive bag. (default: 1)
-A [0|1|2|3] The type of weight setting for each single-instance: 0.keep the weight to be the same as the original value; 1.weight = 1.0 2.weight = 1.0/Total number of single-instance in the corresponding bag 3. weight = Total number of single-instance / (Total number of bags * Total number of single-instance in the corresponding bag). (default: 3)
-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.rules.ZeroR)
Options specific to classifier weka.classifiers.rules.ZeroR:
-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
-
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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weightMethodTipText
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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setWeightMethod
The new method for weighting the instances.- 参数:
method
- the new method
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getWeightMethod
Returns the current weighting method for instances.- 返回:
- the current weighting method
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methodTipText
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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setMethod
Set the method used in testing.- 参数:
method
- the index of method to use.
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getMethod
Get the method used in testing.- 返回:
- the index of method used in testing.
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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:
data
- 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 distribution
- 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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