Package weka.classifiers.pmml.consumer
Class NeuralNetwork
java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.pmml.consumer.PMMLClassifier
weka.classifiers.pmml.consumer.NeuralNetwork
- All Implemented Interfaces:
Serializable,Cloneable,Classifier,BatchPredictor,CapabilitiesHandler,CapabilitiesIgnorer,CommandlineRunnable,OptionHandler,PMMLModel,RevisionHandler
Class implementing import of PMML Neural Network model. Can be used as a Weka
classifier for prediction (buildClassifier() raises an Exception).
- Version:
- $Revision 1.0 $
- 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
ConstructorsConstructorDescriptionNeuralNetwork(Element model, Instances dataDictionary, MiningSchema miningSchema) -
Method Summary
Modifier and TypeMethodDescriptiondouble[]Classifies the given test instance.Returns the revision string.toString()Methods 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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NeuralNetwork
public NeuralNetwork(Element model, Instances dataDictionary, MiningSchema miningSchema) throws Exception - Throws:
Exception
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Method Details
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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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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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toString
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