Package weka.experiment
Class CostSensitiveClassifierSplitEvaluator
java.lang.Object
weka.experiment.ClassifierSplitEvaluator
weka.experiment.CostSensitiveClassifierSplitEvaluator
- All Implemented Interfaces:
Serializable,AdditionalMeasureProducer,OptionHandler,RevisionHandler,SplitEvaluator
SplitEvaluator that produces results for a
classification scheme on a nominal class attribute, including weighted
misclassification costs.
Valid options are:
-W <class name> The full class name of the classifier. eg: weka.classifiers.bayes.NaiveBayes
-C <index> The index of the class for which IR statistics are to be output. (default 1)
-I <index> The index of an attribute to output in the results. This attribute should identify an instance in order to know which instances are in the test set of a cross validation. if 0 no output (default 0).
-P Add target and prediction columns to the result for each fold.
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
-D <directory> Name of a directory to search for cost files when loading costs on demand (default current directory).All options after -- will be passed to the classifier.
- Version:
- $Revision: 11323 $
- Author:
- Len Trigg (len@reeltwo.com)
- See Also:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionReturns the directory that will be searched for cost files when loading on demand.String[]Gets the current settings of the Classifier.Object[]Gets the results for the supplied train and test datasets.String[]Gets the names of each of the result columns produced for a single run.Object[]Gets the data types of each of the result columns produced for a single run.Returns the revision string.Returns a string describing this split evaluatorReturns an enumeration describing the available options..Returns the tip text for this propertyvoidsetOnDemandDirectory(File newDir) Sets the directory that will be searched for cost files when loading on demand.voidsetOptions(String[] options) Parses a given list of options.toString()Returns a text description of the split evaluator.Methods inherited from class weka.experiment.ClassifierSplitEvaluator
classifierTipText, enumerateMeasures, getAttributeID, getClassForIRStatistics, getClassifier, getKey, getKeyNames, getKeyTypes, getMeasure, getNoSizeDetermination, getPredTargetColumn, getRawResultOutput, noSizeDeterminationTipText, setAdditionalMeasures, setAttributeID, setClassForIRStatistics, setClassifier, setClassifierName, setNoSizeDetermination, setPredTargetColumn
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Constructor Details
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CostSensitiveClassifierSplitEvaluator
public CostSensitiveClassifierSplitEvaluator()
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Method Details
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globalInfo
Returns a string describing this split evaluator- Overrides:
globalInfoin classClassifierSplitEvaluator- Returns:
- a description of the split evaluator suitable for displaying in the explorer/experimenter gui
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listOptions
Returns an enumeration describing the available options..- Specified by:
listOptionsin interfaceOptionHandler- Overrides:
listOptionsin classClassifierSplitEvaluator- Returns:
- an enumeration of all the available options.
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setOptions
Parses a given list of options. Valid options are:-W <class name> The full class name of the classifier. eg: weka.classifiers.bayes.NaiveBayes
-C <index> The index of the class for which IR statistics are to be output. (default 1)
-I <index> The index of an attribute to output in the results. This attribute should identify an instance in order to know which instances are in the test set of a cross validation. if 0 no output (default 0).
-P Add target and prediction columns to the result for each fold.
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
-D <directory> Name of a directory to search for cost files when loading costs on demand (default current directory).
All options after -- will be passed to the classifier.- Specified by:
setOptionsin interfaceOptionHandler- Overrides:
setOptionsin classClassifierSplitEvaluator- Parameters:
options- the list of options as an array of strings- Throws:
Exception- if an option is not supported
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getOptions
Gets the current settings of the Classifier.- Specified by:
getOptionsin interfaceOptionHandler- Overrides:
getOptionsin classClassifierSplitEvaluator- Returns:
- an array of strings suitable for passing to setOptions
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onDemandDirectoryTipText
Returns the tip text for this property- Returns:
- tip text for this property suitable for displaying in the explorer/experimenter gui
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getOnDemandDirectory
Returns the directory that will be searched for cost files when loading on demand.- Returns:
- The cost file search directory.
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setOnDemandDirectory
Sets the directory that will be searched for cost files when loading on demand.- Parameters:
newDir- The cost file search directory.
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getResultTypes
Gets the data types of each of the result columns produced for a single run. The number of result fields must be constant for a given SplitEvaluator.- Specified by:
getResultTypesin interfaceSplitEvaluator- Overrides:
getResultTypesin classClassifierSplitEvaluator- Returns:
- an array containing objects of the type of each result column. The objects should be Strings, or Doubles.
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getResultNames
Gets the names of each of the result columns produced for a single run. The number of result fields must be constant for a given SplitEvaluator.- Specified by:
getResultNamesin interfaceSplitEvaluator- Overrides:
getResultNamesin classClassifierSplitEvaluator- Returns:
- an array containing the name of each result column
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getResult
Gets the results for the supplied train and test datasets. Now performs a deep copy of the classifier before it is built and evaluated (just in case the classifier is not initialized properly in buildClassifier()).- Specified by:
getResultin interfaceSplitEvaluator- Overrides:
getResultin classClassifierSplitEvaluator- Parameters:
train- the training Instances.test- the testing Instances.- Returns:
- the results stored in an array. The objects stored in the array may be Strings, Doubles, or null (for the missing value).
- Throws:
Exception- if a problem occurs while getting the results
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toString
Returns a text description of the split evaluator.- Overrides:
toStringin classClassifierSplitEvaluator- Returns:
- a text description of the split evaluator.
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getRevision
Returns the revision string.- Specified by:
getRevisionin interfaceRevisionHandler- Overrides:
getRevisionin classClassifierSplitEvaluator- Returns:
- the revision
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