Package org.processmining.prediction
Class J48Prediction
- java.lang.Object
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- org.processmining.models.FunctionEstimator.AbstractFunctionEstimator
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- org.processmining.models.FunctionEstimator.AbstractDecisionTreeFunctionEstimator
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- org.processmining.models.FunctionEstimator.DecisionTreeFunctionEstimator
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- org.processmining.prediction.J48Prediction
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- All Implemented Interfaces:
org.processmining.models.FunctionEstimator.DecisionTreeBasedFunctionEstimator,org.processmining.models.FunctionEstimator.FunctionEstimator,Leafable
public class J48Prediction extends org.processmining.models.FunctionEstimator.DecisionTreeFunctionEstimator implements Leafable
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Field Summary
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Fields inherited from class org.processmining.models.FunctionEstimator.DecisionTreeFunctionEstimator
classIndexMap, classMapping, classValues, outputClasses
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Fields inherited from class org.processmining.models.FunctionEstimator.AbstractDecisionTreeFunctionEstimator
attributeIndexMap, attributeList, binarySplit, booleanValues, classAttributeName, confidenceThreshold, crossValidate, evaluation, FALSE_VALUE, instances, minNumInstancePerLeaf, name, nullValue, numFoldCrossValidation, numFoldErrorPruning, saveData, tree, TRUE_VALUE, unpruned, variableType
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Constructor Summary
Constructors Constructor Description J48Prediction(java.util.Map<java.lang.String,org.processmining.models.FunctionEstimator.Type> map, java.util.Map<java.lang.String,java.util.Set<java.lang.String>> literalValues, java.lang.Object[] outputValuesAsObjects, java.lang.String name, int capacity, java.util.HashSet<java.lang.String> timeIntervalAttributes)J48Prediction(java.util.Map<java.lang.String,org.processmining.models.FunctionEstimator.Type> map, java.util.Map<java.lang.String,java.util.Set<java.lang.String>> literalValues, java.lang.Object[] outputValuesAsObjects, java.lang.String name, int capacity, java.util.HashSet<java.lang.String> timeIntervalAttributes, boolean balanceInstances)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description voidaddInstance(java.util.Map<java.lang.String,java.lang.Object> variableAssignment, java.lang.Object outputValue, float weight)Adds a new instance to the estimator's 'instances'.voidbalanceInstances()java.util.List<org.processmining.framework.util.Pair<java.lang.String,org.processmining.models.guards.Expression>>getExpressionsAtLeaves()javax.swing.JComponentgetPrefuseTreeVisualization()Returns a JPanel containing a visualization of the weka J48 tree using prefusetreesjavax.swing.JPanelgetVisualization()Returns a JPanel containing a visualization of the weka tree.weka.core.InstancesreturnInstances()-
Methods inherited from class org.processmining.models.FunctionEstimator.DecisionTreeFunctionEstimator
addWekaInstance, computeQualityMeasure, createAttributeList, createClassifier, getClassifier, getClassValue, getFunctionEstimation, isTreatNoLeafAsFalse, setTreatNoLeafAsFalse
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Methods inherited from class org.processmining.models.FunctionEstimator.AbstractDecisionTreeFunctionEstimator
classify, computeFMeasure, createAndSetTree, createInstance, getAttributeByName, getConfidenceThreshold, getEstimation, getEvaluation, getMinNumInstancePerLeaf, getName, getNumFoldCrossValidation, getNumFoldErrorPruning, getNumInstances, getQualityMeasureName, isBinarySplit, isCrossValidate, isUnpruned, saveInstances, setBinarySplit, setConfidenceFactor, setCrossValidate, setMinNumObj, setNumFoldCrossValidation, setNumFolds, setSaveData, setUnpruned, toString
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Methods inherited from class org.processmining.models.FunctionEstimator.AbstractFunctionEstimator
buildExpressionsFromLeafs, convertToExpression, getEstimation
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Constructor Detail
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J48Prediction
public J48Prediction(java.util.Map<java.lang.String,org.processmining.models.FunctionEstimator.Type> map, java.util.Map<java.lang.String,java.util.Set<java.lang.String>> literalValues, java.lang.Object[] outputValuesAsObjects, java.lang.String name, int capacity, java.util.HashSet<java.lang.String> timeIntervalAttributes)
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J48Prediction
public J48Prediction(java.util.Map<java.lang.String,org.processmining.models.FunctionEstimator.Type> map, java.util.Map<java.lang.String,java.util.Set<java.lang.String>> literalValues, java.lang.Object[] outputValuesAsObjects, java.lang.String name, int capacity, java.util.HashSet<java.lang.String> timeIntervalAttributes, boolean balanceInstances)
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Method Detail
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returnInstances
public weka.core.Instances returnInstances()
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getPrefuseTreeVisualization
public javax.swing.JComponent getPrefuseTreeVisualization()
Returns a JPanel containing a visualization of the weka J48 tree using prefusetrees- Overrides:
getPrefuseTreeVisualizationin classorg.processmining.models.FunctionEstimator.AbstractDecisionTreeFunctionEstimator- Returns:
containing a visualization of the decision tree.
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getExpressionsAtLeaves
public java.util.List<org.processmining.framework.util.Pair<java.lang.String,org.processmining.models.guards.Expression>> getExpressionsAtLeaves()
- Specified by:
getExpressionsAtLeavesin interfaceLeafable
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getVisualization
public javax.swing.JPanel getVisualization()
Description copied from class:org.processmining.models.FunctionEstimator.AbstractDecisionTreeFunctionEstimatorReturns a JPanel containing a visualization of the weka tree.- Overrides:
getVisualizationin classorg.processmining.models.FunctionEstimator.AbstractDecisionTreeFunctionEstimator- Returns:
containing a visualization of the decision tree.
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balanceInstances
public void balanceInstances()
- Specified by:
balanceInstancesin interfaceLeafable
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addInstance
public void addInstance(java.util.Map<java.lang.String,java.lang.Object> variableAssignment, java.lang.Object outputValue, float weight)Description copied from class:org.processmining.models.FunctionEstimator.DecisionTreeFunctionEstimatorAdds a new instance to the estimator's 'instances'.- Specified by:
addInstancein interfaceorg.processmining.models.FunctionEstimator.FunctionEstimator- Overrides:
addInstancein classorg.processmining.models.FunctionEstimator.DecisionTreeFunctionEstimator- Parameters:
variableAssignment- A Mapof variable identifier (key) and its value (object). outputValue- The Transition which is to be executed with the variable values of variableAssignment.weight- Parameter for weighted decision trees. Keep 1 for default.
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