类 SimpleMI
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.mi.SimpleMI
- 所有已实现的接口:
Serializable
,Cloneable
,CapabilitiesHandler
,MultiInstanceCapabilitiesHandler
,OptionHandler
,RevisionHandler
public class SimpleMI
extends SingleClassifierEnhancer
implements OptionHandler, MultiInstanceCapabilitiesHandler
Reduces MI data into mono-instance data.
Valid options are:
-M [1|2|3] The method used in transformation: 1.arithmatic average; 2.geometric centor; 3.using minimax combined features of a bag (default: 1) Method 3: Define s to be the vector of the coordinate-wise maxima and minima of X, ie., s(X)=(minx1, ..., minxm, maxx1, ...,maxxm), transform the exemplars into mono-instance which contains attributes s(X)
-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), Lin Dong (ld21@cs.waikato.ac.nz)
- 另请参阅:
-
字段概要
字段修饰符和类型字段说明static final Tag[]
the transformation methodsstatic final int
arithmetic averagestatic final int
geometric averagestatic final int
using minimax combined features of a 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 train) Builds the classifierdouble[]
distributionForInstance
(Instance newBag) Computes the distribution for a given exemplarReturns default capabilities of the classifier.Returns the capabilities of this multi-instance classifier for the relational data.String[]
Gets the current settings of the Classifier.Returns the revision string.Get the method used in transformation.Returns a string describing this filterReturns an enumeration describing the available options.static void
Main method for testing this class.static double[]
Get the minimal and maximal value of a certain attribute in a certain datavoid
setOptions
(String[] options) Parses a given list of options.void
setTransformMethod
(SelectedTag newMethod) Set the method used in transformation.toString()
Gets a string describing the classifier.Implements MITransform (3 type of transformation) 1.arithmatic average; 2.geometric centor; 3.merge minima and maxima attribute value togetherReturns 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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TRANSFORMMETHOD_ARITHMETIC
public static final int TRANSFORMMETHOD_ARITHMETICarithmetic average- 另请参阅:
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TRANSFORMMETHOD_GEOMETRIC
public static final int TRANSFORMMETHOD_GEOMETRICgeometric average- 另请参阅:
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TRANSFORMMETHOD_MINIMAX
public static final int TRANSFORMMETHOD_MINIMAXusing minimax combined features of a bag- 另请参阅:
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TAGS_TRANSFORMMETHOD
the transformation methods
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构造器详细资料
-
SimpleMI
public SimpleMI()
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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
-
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:-M [1|2|3] The method used in transformation: 1.arithmatic average; 2.geometric centor; 3.using minimax combined features of a bag (default: 1) Method 3: Define s to be the vector of the coordinate-wise maxima and minima of X, ie., s(X)=(minx1, ..., minxm, maxx1, ...,maxxm), transform the exemplars into mono-instance which contains attributes s(X)
-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
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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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transformMethodTipText
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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setTransformMethod
Set the method used in transformation.- 参数:
newMethod
- the index of method to use.
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getTransformMethod
Get the method used in transformation.- 返回:
- the index of method used.
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transform
Implements MITransform (3 type of transformation) 1.arithmatic average; 2.geometric centor; 3.merge minima and maxima attribute value together- 参数:
train
- the multi-instance dataset (with relational attribute)- 返回:
- the transformed dataset with each bag contain mono-instance (without relational attribute) so that any classifier not for MI dataset can be applied on it.
- 抛出:
Exception
- if the transformation fails
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minimax
Get the minimal and maximal value of a certain attribute in a certain data- 参数:
data
- the dataattIndex
- the index of the attribute- 返回:
- the double array containing in entry 0 for min and 1 for max.
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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:
-
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:
-
buildClassifier
Builds the classifier- 指定者:
buildClassifier
在类中Classifier
- 参数:
train
- 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:
newBag
- 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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