Package weka.classifiers.pmml.consumer
Class RuleSetModel
java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.pmml.consumer.PMMLClassifier
weka.classifiers.pmml.consumer.RuleSetModel
- All Implemented Interfaces:
Serializable
,Cloneable
,Classifier
,BatchPredictor
,CapabilitiesHandler
,CapabilitiesIgnorer
,CommandlineRunnable
,OptionHandler
,PMMLModel
,RevisionHandler
Class implementing import of PMML RuleSetModel. Can be used as a Weka
classifier for prediction only (buildClassifier() raises an Exception).
- 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
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Constructor Summary
ConstructorDescriptionRuleSetModel
(Element model, Instances dataDictionary, MiningSchema miningSchema) Constructor for a RuleSetModel -
Method Summary
Modifier and TypeMethodDescriptiondouble[]
Classifies the given test instance.Get the revision string for this classtoString()
Return a textual description of this model.Methods inherited from class weka.classifiers.pmml.consumer.PMMLClassifier
buildClassifier, done, getCreatorApplication, getDataDictionary, getFieldsMappingString, getLog, getMiningSchema, getPMMLVersion, mapToMiningSchema, setCreatorApplication, setLog, setPMMLVersion
Methods 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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RuleSetModel
public RuleSetModel(Element model, Instances dataDictionary, MiningSchema miningSchema) throws Exception Constructor for a RuleSetModel- Parameters:
model
- the XML element encapsulating the RuleSetModeldataDictionary
- the data dictionary to useminingSchema
- the mining schema to use- Throws:
Exception
- if something goes wrong
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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:
distributionForInstance
in interfaceClassifier
- Overrides:
distributionForInstance
in 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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toString
Return a textual description of this model. -
getRevision
Get the revision string for this class- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classAbstractClassifier
- Returns:
- the revision string
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