Package weka.classifiers.meta
Class WeightedInstancesHandlerWrapper
java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.SingleClassifierEnhancer
weka.classifiers.RandomizableSingleClassifierEnhancer
weka.classifiers.meta.WeightedInstancesHandlerWrapper
- All Implemented Interfaces:
Serializable,Cloneable,Classifier,BatchPredictor,CapabilitiesHandler,CapabilitiesIgnorer,CommandlineRunnable,OptionHandler,Randomizable,RevisionHandler,WeightedInstancesHandler
public class WeightedInstancesHandlerWrapper
extends RandomizableSingleClassifierEnhancer
implements WeightedInstancesHandler
Generic wrapper around any classifier to enable weighted instances support.
Uses resampling with weights if the base classifier is not implementing the weka.core.WeightedInstancesHandler interface and there are instance weights other 1.0 present. By default, the training data is passed through to the base classifier if it can handle instance weights. However, it is possible to force the use of resampling with weights as well.
Valid options are:
Uses resampling with weights if the base classifier is not implementing the weka.core.WeightedInstancesHandler interface and there are instance weights other 1.0 present. By default, the training data is passed through to the base classifier if it can handle instance weights. However, it is possible to force the use of resampling with weights as well.
Valid options are:
-force-resample-with-weights Forces resampling of weights, regardless of whether base classifier handles instance weights
-S <num> Random number seed. (default 1)
-W Full name of base classifier. (default: weka.classifiers.rules.ZeroR)
-output-debug-info If set, classifier is run in debug mode and may output additional info to the console
-do-not-check-capabilities If set, classifier capabilities are not checked before classifier is built (use with caution).
-num-decimal-places The number of decimal places for the output of numbers in the model (default 2).
Options specific to classifier weka.classifiers.rules.ZeroR:
-output-debug-info If set, classifier is run in debug mode and may output additional info to the console
-do-not-check-capabilities If set, classifier capabilities are not checked before classifier is built (use with caution).
-num-decimal-places The number of decimal places for the output of numbers in the model (default 2).
- Version:
- $Revision: 12226 $
- Author:
- FracPete (fracpete at waikato dot ac dot nz)
- See Also:
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Field Summary
FieldsModifier and TypeFieldDescriptionstatic final Stringcommand-line option for resampling with weights.Fields inherited from class weka.classifiers.AbstractClassifier
BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoidbuildClassifier(Instances data) builds the classifier.doubleclassifyInstance(Instance instance) Classifies the given test instance.double[]distributionForInstance(Instance instance) Calculates the class membership probabilities for the given test instance.Returns the tip text for this propertybooleanGets the size of each subSpace, as a percentage of the training set size.String[]Gets the current settings of the Classifier.Returns the revision string.Returns a string describing classifierReturns an enumeration describing the available options.static voidMain method for testing this class.voidsetForceResampleWithWeights(boolean value) Sets the size of each subSpace, as a percentage of the training set size.voidsetOptions(String[] options) Parses a given list of options.toString()Returns a string description of the model.Methods inherited from class weka.classifiers.RandomizableSingleClassifierEnhancer
getSeed, seedTipText, setSeedMethods inherited from class weka.classifiers.SingleClassifierEnhancer
classifierTipText, getCapabilities, getClassifier, postExecution, preExecution, setClassifierMethods inherited from class weka.classifiers.AbstractClassifier
batchSizeTipText, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces
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Field Details
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FORCE_RESAMPLE_WITH_WEIGHTS
command-line option for resampling with weights.- See Also:
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Constructor Details
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WeightedInstancesHandlerWrapper
public WeightedInstancesHandlerWrapper()
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Method Details
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globalInfo
Returns a string describing classifier- Returns:
- a description 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 classRandomizableSingleClassifierEnhancer- Returns:
- an enumeration of all the available options.
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setOptions
Parses a given list of options.- Specified by:
setOptionsin interfaceOptionHandler- Overrides:
setOptionsin classRandomizableSingleClassifierEnhancer- 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 classRandomizableSingleClassifierEnhancer- Returns:
- an array of strings suitable for passing to setOptions
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getForceResampleWithWeights
public boolean getForceResampleWithWeights()Gets the size of each subSpace, as a percentage of the training set size.- Returns:
- the subSpace size, as a percentage.
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setForceResampleWithWeights
public void setForceResampleWithWeights(boolean value) Sets the size of each subSpace, as a percentage of the training set size.- Parameters:
value- the subSpace size, as a percentage.
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forceResampleWithWeightsTipText
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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buildClassifier
builds the classifier.- Specified by:
buildClassifierin interfaceClassifier- Parameters:
data- the training data to be used for generating the classifier.- Throws:
Exception- if the classifier could not be built successfully
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distributionForInstance
Calculates the class membership probabilities for the given test instance.- Specified by:
distributionForInstancein interfaceClassifier- Overrides:
distributionForInstancein classAbstractClassifier- Parameters:
instance- the instance to be classified- Returns:
- preedicted class probability distribution
- Throws:
Exception- if distribution can't be computed successfully
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classifyInstance
Classifies the given test instance.- Specified by:
classifyInstancein interfaceClassifier- Overrides:
classifyInstancein classAbstractClassifier- Parameters:
instance- the instance to be classified- Returns:
- the predicted most likely class for the instance or Utils.missingValue() if no prediction is made
- Throws:
Exception- if an error occurred during the prediction
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toString
Returns a string description of the model. -
getRevision
Returns the revision string.- Specified by:
getRevisionin interfaceRevisionHandler- Overrides:
getRevisionin classAbstractClassifier- Returns:
- the revision
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main
Main method for testing this class.- Parameters:
args- the options
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