Package weka.classifiers.pmml.consumer
Class TreeModel
java.lang.Object
weka.classifiers.AbstractClassifier
weka.classifiers.pmml.consumer.PMMLClassifier
weka.classifiers.pmml.consumer.TreeModel
- All Implemented Interfaces:
Serializable
,Cloneable
,Classifier
,BatchPredictor
,CapabilitiesHandler
,CapabilitiesIgnorer
,CommandlineRunnable
,Drawable
,OptionHandler
,PMMLModel
,RevisionHandler
Class implementing import of PMML TreeModel. Can be used as a Weka classifier
for prediction (buildClassifier() raises and Exception).
- Version:
- $Revision: 10153 $;
- 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
Fields inherited from interface weka.core.Drawable
BayesNet, Newick, NOT_DRAWABLE, TREE
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Constructor Summary
ConstructorDescriptionTreeModel
(Element model, Instances dataDictionary, MiningSchema miningSchema) -
Method Summary
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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TreeModel
public TreeModel(Element model, Instances dataDictionary, MiningSchema miningSchema) throws Exception - Throws:
Exception
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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
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graph
Description copied from interface:Drawable
Returns a string that describes a graph representing the object. The string should be in XMLBIF ver. 0.3 format if the graph is a BayesNet, otherwise it should be in dotty format. -
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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graphType
public int graphType()Description copied from interface:Drawable
Returns the type of graph representing the object.
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