Package weka.classifiers.pmml.consumer
Class SupportVectorMachineModel
java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.pmml.consumer.PMMLClassifier
weka.classifiers.pmml.consumer.SupportVectorMachineModel
- All Implemented Interfaces:
Serializable,Cloneable,Classifier,BatchPredictor,CapabilitiesHandler,CapabilitiesIgnorer,CommandlineRunnable,OptionHandler,PMMLModel,RevisionHandler
Implements a PMML SupportVectorMachineModel
- Version:
- $Revision: 8034 $
- Author:
- Mark Hall (mhall{[at]}pentaho{[dot]}com)
- See Also:
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Field Summary
Fields inherited from class weka.classifiers.AbstractClassifier
BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT -
Constructor Summary
ConstructorsConstructorDescriptionSupportVectorMachineModel(Element model, Instances dataDictionary, MiningSchema miningSchema) Construct a new SupportVectorMachineModel encapsulating the information provided in the PMML document. -
Method Summary
Modifier and TypeMethodDescriptiondouble[]Classifies the given test instance.Returns the revision string.toString()Get a textual description of this SupportVectorMachineModelMethods inherited from class weka.classifiers.pmml.consumer.PMMLClassifier
buildClassifier, done, getCreatorApplication, getDataDictionary, getFieldsMappingString, getLog, getMiningSchema, getPMMLVersion, mapToMiningSchema, setCreatorApplication, setLog, setPMMLVersionMethods inherited from class weka.classifiers.AbstractClassifier
batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getCapabilities, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, getOptions, implementsMoreEfficientBatchPrediction, listOptions, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces, setOptions
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Constructor Details
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SupportVectorMachineModel
public SupportVectorMachineModel(Element model, Instances dataDictionary, MiningSchema miningSchema) throws Exception Construct a new SupportVectorMachineModel encapsulating the information provided in the PMML document.- Parameters:
model- the SVM element from the PMML documentdataDictionary- the data dictionaryminingSchema- the mining schema- Throws:
Exception- if the model can't be constructed from the PMML
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Method Details
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distributionForInstance
Classifies the given test instance. The instance has to belong to a dataset when it's being classified.- Specified by:
distributionForInstancein interfaceClassifier- Overrides:
distributionForInstancein classAbstractClassifier- Parameters:
inst- 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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getRevision
Description copied from class:AbstractClassifierReturns the revision string.- Specified by:
getRevisionin interfaceRevisionHandler- Overrides:
getRevisionin classAbstractClassifier- Returns:
- the revision
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toString
Get a textual description of this SupportVectorMachineModel
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