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
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Constructor Summary
ConstructorDescriptionNeuralNetwork
(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, 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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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:AbstractClassifier
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in 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:
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
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