类 DTNB
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.rules.DecisionTable
weka.classifiers.rules.DTNB
- 所有已实现的接口:
Serializable
,Cloneable
,AdditionalMeasureProducer
,CapabilitiesHandler
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
,WeightedInstancesHandler
Class for building and using a decision table/naive bayes hybrid classifier. At each point in the search, the algorithm evaluates the merit of dividing the attributes into two disjoint subsets: one for the decision table, the other for naive Bayes. A forward selection search is used, where at each step, selected attributes are modeled by naive Bayes and the remainder by the decision table, and all attributes are modelled by the decision table initially. At each step, the algorithm also considers dropping an attribute entirely from the model.
For more information, see:
Mark Hall, Eibe Frank: Combining Naive Bayes and Decision Tables. In: Proceedings of the 21st Florida Artificial Intelligence Society Conference (FLAIRS), ???-???, 2008. BibTeX:
For more information, see:
Mark Hall, Eibe Frank: Combining Naive Bayes and Decision Tables. In: Proceedings of the 21st Florida Artificial Intelligence Society Conference (FLAIRS), ???-???, 2008. BibTeX:
@inproceedings{Hall2008, author = {Mark Hall and Eibe Frank}, booktitle = {Proceedings of the 21st Florida Artificial Intelligence Society Conference (FLAIRS)}, pages = {318-319}, publisher = {AAAI press}, title = {Combining Naive Bayes and Decision Tables}, year = {2008} }Valid options are:
-X <number of folds> Use cross validation to evaluate features. Use number of folds = 1 for leave one out CV. (Default = leave one out CV)
-E <acc | rmse | mae | auc> Performance evaluation measure to use for selecting attributes. (Default = accuracy for discrete class and rmse for numeric class)
-I Use nearest neighbour instead of global table majority.
-R Display decision table rules.
- 版本:
- $Revision: 6269 $
- 作者:
- Mark Hall (mhall{[at]}pentaho{[dot]}org), Eibe Frank (eibe{[at]}cs{[dot]}waikato{[dot]}ac{[dot]}nz)
- 另请参阅:
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字段概要
从类继承的字段 weka.classifiers.rules.DecisionTable
EVAL_ACCURACY, EVAL_AUC, EVAL_DEFAULT, EVAL_MAE, EVAL_RMSE, TAGS_EVALUATION
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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) Generates the classifier.double[]
distributionForInstance
(Instance instance) Calculates the class membership probabilities for the given test instance.Returns an enumeration of the additional measure namesReturns default capabilities of the classifier.double
getMeasure
(String additionalMeasureName) Returns the value of the named measureString[]
Gets the current settings of the classifier.Returns the revision string.Gets the current search methodReturns 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 options.static void
Main method for testing this class.double
Returns the number of rulesvoid
setOptions
(String[] options) Parses the options for this object.void
Sets the search method to usetoString()
Returns a description of the classifier.从类继承的方法 weka.classifiers.rules.DecisionTable
crossValTipText, displayRulesTipText, evaluationMeasureTipText, getCrossVal, getDisplayRules, getEvaluationMeasure, getUseIBk, measureNumRules, printFeatures, searchTipText, setCrossVal, setDisplayRules, setEvaluationMeasure, setUseIBk, useIBkTipText
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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DTNB
public DTNB()
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方法详细资料
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globalInfo
Returns a string describing classifier- 覆盖:
globalInfo
在类中DecisionTable
- 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
- 覆盖:
getTechnicalInformation
在类中DecisionTable
- 返回:
- the technical information about this class
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buildClassifier
Generates the classifier.- 覆盖:
buildClassifier
在类中DecisionTable
- 参数:
data
- set of instances serving as training data- 抛出:
Exception
- if the classifier has not been generated successfully
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distributionForInstance
Calculates the class membership probabilities for the given test instance.- 覆盖:
distributionForInstance
在类中DecisionTable
- 参数:
instance
- the instance to be classified- 返回:
- predicted class probability distribution
- 抛出:
Exception
- if distribution can't be computed
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toString
从类复制的说明:DecisionTable
Returns a description of the classifier.- 覆盖:
toString
在类中DecisionTable
- 返回:
- a description of the classifier as a string.
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measurePercentAttsUsedByDT
public double measurePercentAttsUsedByDT()Returns the number of rules- 返回:
- the number of rules
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enumerateMeasures
Returns an enumeration of the additional measure names- 指定者:
enumerateMeasures
在接口中AdditionalMeasureProducer
- 覆盖:
enumerateMeasures
在类中DecisionTable
- 返回:
- an enumeration of the measure names
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getMeasure
Returns the value of the named measure- 指定者:
getMeasure
在接口中AdditionalMeasureProducer
- 覆盖:
getMeasure
在类中DecisionTable
- 参数:
additionalMeasureName
- the name of the measure to query for its value- 返回:
- the value of the named measure
- 抛出:
IllegalArgumentException
- if the named measure is not supported
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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DecisionTable
- 返回:
- the capabilities of this classifier
- 另请参阅:
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setSearch
Sets the search method to use- 覆盖:
setSearch
在类中DecisionTable
- 参数:
search
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getSearch
Gets the current search method- 覆盖:
getSearch
在类中DecisionTable
- 返回:
- the search method used
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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DecisionTable
- 返回:
- an enumeration of all the available options.
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setOptions
Parses the options for this object. Valid options are:-X <number of folds> Use cross validation to evaluate features. Use number of folds = 1 for leave one out CV. (Default = leave one out CV)
-E <acc | rmse | mae | auc> Performance evaluation measure to use for selecting attributes. (Default = accuracy for discrete class and rmse for numeric class)
-I Use nearest neighbour instead of global table majority.
-R Display decision table rules.
- 指定者:
setOptions
在接口中OptionHandler
- 覆盖:
setOptions
在类中DecisionTable
- 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DecisionTable
- 返回:
- an array of strings suitable for passing to setOptions
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getRevision
Returns the revision string.- 指定者:
getRevision
在接口中RevisionHandler
- 覆盖:
getRevision
在类中DecisionTable
- 返回:
- the revision
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main
Main method for testing this class.- 参数:
argv
- the command-line options
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