@Deprecated public class RandomTreeFunctionEstimator extends DecisionTreeFunctionEstimator
classIndexMap, classMapping, classValues, outputClasses
attributeIndexMap, attributeList, binarySplit, booleanValues, classAttributeName, confidenceThreshold, crossValidate, evaluation, FALSE_VALUE, instances, minNumInstancePerLeaf, name, nullValue, numFoldCrossValidation, numFoldErrorPruning, saveData, tree, TRUE_VALUE, unpruned, variableType
Constructor and Description |
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RandomTreeFunctionEstimator(java.util.Map<java.lang.String,org.processmining.models.FunctionEstimator.Type> attributeType,
java.util.Map<java.lang.String,java.util.Set<java.lang.String>> literalValues,
java.lang.Object[] outputClasses,
java.lang.String name,
int capacity)
Deprecated.
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Modifier and Type | Method and Description |
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protected weka.classifiers.AbstractClassifier |
createClassifier(java.lang.Object[] option,
boolean saveData)
Deprecated.
Creates the RepTree using the earlier supplied options.
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addInstance, addWekaInstance, computeQualityMeasure, createAttributeList, getClassifier, getClassValue, getFunctionEstimation, isTreatNoLeafAsFalse, setTreatNoLeafAsFalse
classify, computeFMeasure, createAndSetTree, createInstance, getAttributeByName, getConfidenceThreshold, getEstimation, getEvaluation, getMinNumInstancePerLeaf, getName, getNumFoldCrossValidation, getNumFoldErrorPruning, getNumInstances, getPrefuseTreeVisualization, getQualityMeasureName, getVisualization, isBinarySplit, isCrossValidate, isUnpruned, saveInstances, setBinarySplit, setConfidenceFactor, setCrossValidate, setMinNumObj, setNumFoldCrossValidation, setNumFolds, setSaveData, setUnpruned, toString
buildExpressionsFromLeafs, convertToExpression, getEstimation
public RandomTreeFunctionEstimator(java.util.Map<java.lang.String,org.processmining.models.FunctionEstimator.Type> attributeType, java.util.Map<java.lang.String,java.util.Set<java.lang.String>> literalValues, java.lang.Object[] outputClasses, java.lang.String name, int capacity)
protected weka.classifiers.AbstractClassifier createClassifier(java.lang.Object[] option, boolean saveData) throws java.lang.Exception
DecisionTreeFunctionEstimator
createClassifier
in class DecisionTreeFunctionEstimator
option
- Array of Strings containing J48 tree options.saveData
- Boolean. True to enable saving instance data to the tree.java.lang.Exception
- if classifier can't be built correctly