类 OneRAttributeEval
java.lang.Object
weka.attributeSelection.ASEvaluation
weka.attributeSelection.OneRAttributeEval
OneRAttributeEval :
Evaluates the worth of an attribute by using the OneR classifier.
Valid options are:
Evaluates the worth of an attribute by using the OneR classifier.
Valid options are:
-S <seed> Random number seed for cross validation (default = 1)
-F <folds> Number of folds for cross validation (default = 10)
-D Use training data for evaluation rather than cross validaton
-B <minimum bucket size> Minimum number of objects in a bucket (passed on to OneR, default = 6)
- 版本:
- $Revision: 11219 $
- 作者:
- Mark Hall (mhall@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
buildEvaluator
(Instances data) Initializes a OneRAttribute attribute evaluator.double
evaluateAttribute
(int attribute) evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.Returns a string for this option suitable for display in the gui as a tip textReturns a string for this option suitable for display in the gui as a tip textReturns the capabilities of this evaluator.boolean
Returns true if the training data is to be used for evaluationint
getFolds()
Get the number of folds used for cross validationint
Get the minimum bucket size used by oneRString[]
returns the current setup.Returns the revision string.int
getSeed()
Get the random number seedReturns a string describing this attribute evaluatorReturns an enumeration describing the available options.static void
Main method for testing this class.Returns a string for this option suitable for display in the gui as a tip textint[]
postProcess
(int[] attributeSet) Provides a chance for a attribute evaluator to do any special post processing of the selected attribute set.Returns a string for this option suitable for display in the gui as a tip textvoid
setEvalUsingTrainingData
(boolean e) Use the training data to evaluate attributes rather than cross validationvoid
setFolds
(int folds) Set the number of folds to use for cross validationvoid
setMinimumBucketSize
(int minB) Set the minumum bucket size used by OneRvoid
setOptions
(String[] options) Parses a given list of options.void
setSeed
(int seed) Set the random number seed for cross validationtoString()
Return a description of the evaluator从类继承的方法 weka.attributeSelection.ASEvaluation
clean, forName, makeCopies
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构造器详细资料
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OneRAttributeEval
public OneRAttributeEval()Constructor
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方法详细资料
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globalInfo
Returns a string describing this attribute evaluator- 返回:
- a description of the evaluator suitable for displaying in the explorer/experimenter gui
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seedTipText
Returns a string for this option suitable for display in the gui as a tip text- 返回:
- a string describing this option
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setSeed
public void setSeed(int seed) Set the random number seed for cross validation- 参数:
seed
- the seed to use
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getSeed
public int getSeed()Get the random number seed- 返回:
- an
int
value
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foldsTipText
Returns a string for this option suitable for display in the gui as a tip text- 返回:
- a string describing this option
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setFolds
public void setFolds(int folds) Set the number of folds to use for cross validation- 参数:
folds
- the number of folds
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getFolds
public int getFolds()Get the number of folds used for cross validation- 返回:
- the number of folds
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evalUsingTrainingDataTipText
Returns a string for this option suitable for display in the gui as a tip text- 返回:
- a string describing this option
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setEvalUsingTrainingData
public void setEvalUsingTrainingData(boolean e) Use the training data to evaluate attributes rather than cross validation- 参数:
e
- true if training data is to be used for evaluation
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minimumBucketSizeTipText
Returns a string for this option suitable for display in the gui as a tip text- 返回:
- a string describing this option
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setMinimumBucketSize
public void setMinimumBucketSize(int minB) Set the minumum bucket size used by OneR- 参数:
minB
- the minimum bucket size to use
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getMinimumBucketSize
public int getMinimumBucketSize()Get the minimum bucket size used by oneR- 返回:
- the minimum bucket size used
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getEvalUsingTrainingData
public boolean getEvalUsingTrainingData()Returns true if the training data is to be used for evaluation- 返回:
- true if training data is to be used for evaluation
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listOptions
Returns an enumeration describing the available options.- 指定者:
listOptions
在接口中OptionHandler
- 返回:
- an enumeration of all the available options.
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setOptions
Parses a given list of options. Valid options are:-S <seed> Random number seed for cross validation (default = 1)
-F <folds> Number of folds for cross validation (default = 10)
-D Use training data for evaluation rather than cross validaton
-B <minimum bucket size> Minimum number of objects in a bucket (passed on to OneR, default = 6)
- 指定者:
setOptions
在接口中OptionHandler
- 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
returns the current setup.- 指定者:
getOptions
在接口中OptionHandler
- 返回:
- the options of the current setup
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getCapabilities
Returns the capabilities of this evaluator.- 指定者:
getCapabilities
在接口中CapabilitiesHandler
- 覆盖:
getCapabilities
在类中ASEvaluation
- 返回:
- the capabilities of this evaluator
- 另请参阅:
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buildEvaluator
Initializes a OneRAttribute attribute evaluator. Discretizes all attributes that are numeric.- 指定者:
buildEvaluator
在类中ASEvaluation
- 参数:
data
- set of instances serving as training data- 抛出:
Exception
- if the evaluator has not been generated successfully
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evaluateAttribute
evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.- 指定者:
evaluateAttribute
在接口中AttributeEvaluator
- 参数:
attribute
- the index of the attribute to be evaluated- 返回:
- the "merit" of the attribute
- 抛出:
Exception
- if the attribute could not be evaluated
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toString
Return a description of the evaluator -
getRevision
Returns the revision string.- 指定者:
getRevision
在接口中RevisionHandler
- 覆盖:
getRevision
在类中ASEvaluation
- 返回:
- the revision
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postProcess
public int[] postProcess(int[] attributeSet) 从类复制的说明:ASEvaluation
Provides a chance for a attribute evaluator to do any special post processing of the selected attribute set.- 覆盖:
postProcess
在类中ASEvaluation
- 参数:
attributeSet
- the set of attributes found by the search- 返回:
- a possibly ranked list of postprocessed attributes
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main
Main method for testing this class.- 参数:
args
- the options
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