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A

aaPairs - Variable in class org.processmining.pmind.models.DMNModel
 
AbstractDMNMiner - Class in org.processmining.pmind.algorithms
 
AbstractDMNMiner(XLog, PMInDParameters) - Constructor for class org.processmining.pmind.algorithms.AbstractDMNMiner
 
activities - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
activities - Variable in class org.processmining.pmind.models.DMNModel
 
Activity - Class in org.processmining.pmind.models
 
Activity(XEventClass, Set<DMNAttribute>, boolean, boolean) - Constructor for class org.processmining.pmind.models.Activity
 
activity - Variable in class org.processmining.pmind.models.DMNActivity
 
ActivityDataStore - Class in org.processmining.pmind.algorithms.concept
 
ActivityDataStore(Set<DMNAttribute>) - Constructor for class org.processmining.pmind.algorithms.concept.ActivityDataStore
 
add(Instance) - Method in class weka.core.Instances
Adds one instance to the end of the set.
add(int, Instance) - Method in class weka.core.Instances
Adds one instance at the given position in the list.
addASS(AttributeShiftSequence) - Method in class org.processmining.pmind.models.DMNAttribute
 
addAttributePositionInformationToLog(XLog, boolean, int) - Static method in class org.processmining.pmind.logs.EventLogOperations
 
addDAAP(DMNActivityAttributePair) - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
addDataElement(DMNAttribute, String, int) - Method in class org.processmining.pmind.algorithms.concept.ActivityDataStore
 
addDotNode(DotNode) - Method in class org.processmining.pmind.models.DMNNode
 
addEdge(DMNNode, DMNNode) - Method in class org.processmining.pmind.models.DMNModel
 
addEdge(DMNNode, DMNNode, int, double) - Method in class org.processmining.pmind.models.DMNModel
 
addEvent(XEvent, XEvent, XEvent, int, int, XLogInfo) - Method in class org.processmining.pmind.models.Activity
 
addInstance(Map<String, Object>, Object, float) - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
Adds a new instance to the estimator's 'instances'.
addKnowledgeNode(String, DMNActivityAttributePair) - Method in class org.processmining.pmind.models.DMNModel
 
addNode(DMNActivityAttributePair) - Method in class org.processmining.pmind.models.DMNModel
 
addNode(DMNActivityAttributePair, String) - Method in class org.processmining.pmind.models.DMNModel
 
addNode(DMNAttribute) - Method in class org.processmining.pmind.models.DMNModel
 
addNode(DMNAttribute, String) - Method in class org.processmining.pmind.models.DMNModel
 
addNodes(int, DMNModel, DMNActivityAttributePair, PossibleModel) - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
addNumericTrainClass(double, double) - Method in class weka.classifiers.evaluation.Evaluation
Adds a numeric (non-missing) training class value and weight to the buffer of stored values.
addOutputDependencies(Map<Activity, Double>) - Method in class org.processmining.pmind.models.DMNAttribute
 
addPetrinet(Object[]) - Method in class org.processmining.pmind.models.DMNModel
 
addReplayResult(DMNActivityAttributePair, String) - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
addSubModel(ModelComparison) - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
addSubModel(DMNModel) - Method in class org.processmining.pmind.models.DMNModel
 
addSubModels(Set<ModelComparison>) - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
addTrainedModel(Pair<DMNActivity, DMNAttribute>) - Method in class org.processmining.pmind.models.DMNModel
 
addValueOfTrace(int, String) - Method in class org.processmining.pmind.models.DMNAttribute
 
addWekaInstance(Instance, Object, float) - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 
analyzeAttributes(double) - Method in class org.processmining.pmind.models.Activity
 
analyzeModels() - Method in class org.processmining.pmind.algorithms.PMInDModelChecker
 
areaUnderPRC(int) - Method in class weka.classifiers.evaluation.Evaluation
Returns the area under precision-recall curve (AUPRC) for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
areaUnderROC(int) - Method in class weka.classifiers.evaluation.Evaluation
Returns the area under ROC for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
areConnected(DMNNode, DMNNode) - Method in class org.processmining.pmind.models.DMNModel
 
areConnected(DMNActivityAttributePair, DMNActivityAttributePair, boolean) - Method in class org.processmining.pmind.models.DMNModel
 
areConnected(DMNDecisionActivity, DMNDecisionActivity) - Method in class org.processmining.pmind.models.DMNModel
 
areConnected(DMNActivityAttributePair, Activity, DMNAttribute, int) - Method in class org.processmining.pmind.models.DMNModel
 
ARFF_DATA - Static variable in class weka.core.Instances
The keyword used to denote the start of the arff data section
ARFF_RELATION - Static variable in class weka.core.Instances
The keyword used to denote the start of an arff header
attribute(int) - Method in class weka.core.Instances
Returns an attribute.
attribute(String) - Method in class weka.core.Instances
Returns an attribute given its name.
attributes - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
attributes - Variable in class org.processmining.pmind.models.DMNModel
 
AttributeShiftSequence - Class in org.processmining.pmind.algorithms.concept
 
AttributeShiftSequence(Collection<Shift>) - Constructor for class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
attributeStats(int) - Method in class weka.core.Instances
Calculates summary statistics on the values that appear in this set of instances for a specified attribute.
attributeToDoubleArray(int) - Method in class weka.core.Instances
Gets the value of all instances in this dataset for a particular attribute.
avgCost() - Method in class weka.classifiers.evaluation.Evaluation
Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.

B

buildModel(PossibleModel, boolean) - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
buildModelForActivities() - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
buildModelForActivities() - Method in class org.processmining.pmind.algorithms.DMNMinerShiftBasedOld
 
buildModelForActivities() - Method in class org.processmining.pmind.algorithms.PMInDNoShifts
 
buildModelForActivities() - Method in class org.processmining.pmind.algorithms.PMInDShiftBased
 
buildModelForActivities() - Method in class org.processmining.pmind.algorithms.SOAPMInD
 
BUILT_IN_EVAL_METRICS - Static variable in class weka.classifiers.evaluation.Evaluation
 

C

calculateAutoCorrAll(ArrayList<ArrayList<String>>, String, int) - Method in class org.processmining.pmind.algorithms.autocorrelations.CorrelationsCalculator
 
calculateAutoCorrTrace(int, ArrayList<ArrayList<String>>, String, int) - Method in class org.processmining.pmind.algorithms.autocorrelations.CorrelationsCalculator
 
calculateCorrelation(DMNAttribute, DMNAttribute) - Static method in class org.processmining.pmind.algorithms.autocorrelations.CorrelationsCalculator
 
calculateCorrelation(ArrayList<String>, ArrayList<String>, boolean) - Static method in class org.processmining.pmind.algorithms.autocorrelations.CorrelationsCalculator
 
checkForAttributeType(int) - Method in class weka.core.Instances
Checks for attributes of the given type in the dataset
checkForStringAttributes() - Method in class weka.core.Instances
Checks for string attributes in the dataset
checkInstance(Instance) - Method in class weka.core.Instances
Checks if the given instance is compatible with this dataset.
checkModels(DMNModel, DMNModel) - Method in class org.processmining.pmind.algorithms.PMInDModelChecker
 
checkModels(DMNModel, DMNModel) - Method in class org.processmining.pmind.plugins.PMInDCheckerVisualizer
 
classAttribute() - Method in class weka.core.Instances
Returns the class attribute.
classifyInstance(Map<String, Object>) - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 
classIndex() - Method in class weka.core.Instances
Returns the class attribute's index.
classIndexMap - Variable in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 
classMapping - Variable in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 
classValues - Variable in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 
clone(String, Set<Integer>) - Method in class org.processmining.pmind.models.DMNModel
 
cloneFrom(DirectedGraph<DMNNode, DMNEdge>) - Method in class org.processmining.pmind.models.DMNModel
 
colorMissingElements(DMNModel, DMNModel, String) - Method in class org.processmining.pmind.plugins.PMInDCheckerVisualizer
 
colorNodes(HashSet<Activity>, HashSet<Activity>, Dot) - Static method in class org.processmining.pmind.plugins.PMInDOutputVisualizer
 
compactify() - Method in class weka.core.Instances
Compactifies the set of instances.
compareTo(PossibleModel) - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
compareTo(Shift) - Method in class org.processmining.pmind.algorithms.concept.Shift
 
compareTo(DMNActivityAttributePair) - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
computeQualityMeasure() - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 
confusionMatrix() - Method in class weka.classifiers.evaluation.Evaluation
Returns a copy of the confusion matrix.
ConstructCorrelationsForEventAttributes - Class in org.processmining.pmind.plugins
 
ConstructCorrelationsForEventAttributes() - Constructor for class org.processmining.pmind.plugins.ConstructCorrelationsForEventAttributes
 
contains(PossibleModel) - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
contains(Object) - Method in class org.processmining.pmind.models.DMNModel
 
copyInstances(int, Instances, int) - Method in class weka.core.Instances
Copies instances from one set to the end of another one.
correct() - Method in class weka.classifiers.evaluation.Evaluation
Gets the number of instances correctly classified (that is, for which a correct prediction was made).
correlationCoefficient() - Method in class weka.classifiers.evaluation.Evaluation
Returns the correlation coefficient if the class is numeric.
CorrelationsCalculator - Class in org.processmining.pmind.algorithms.autocorrelations
 
CorrelationsCalculator(XLog, Collection<DMNAttribute>, HashMap<XEventClass, Activity>, double, double) - Constructor for class org.processmining.pmind.algorithms.autocorrelations.CorrelationsCalculator
 
coverageOfTestCasesByPredictedRegions() - Method in class weka.classifiers.evaluation.Evaluation
Gets the coverage of the test cases by the predicted regions at the confidence level specified when evaluation was performed.
createAttributeList(Map<String, Type>, Map<String, Set<String>>, Object[]) - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 
createClassifier(Object[], boolean) - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
Creates the RepTree using the earlier supplied options.
createEventLogOfShifts(XLog, XLogInfo, XEventClassifier, HashMap<XEventClass, Activity>) - Static method in class org.processmining.pmind.logs.EventLogOperations
 
createTrainingSet(PossibleModel) - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
crossValidateModel(Classifier, Instances, int, Random, Object...) - Method in class weka.classifiers.evaluation.Evaluation
Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(String, Instances, int, String[], Random) - Method in class weka.classifiers.evaluation.Evaluation
Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.

D

daapToAt - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
daikonMiner(UIPluginContext, PetrinetGraph, XLog) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
data - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
datToMat(Instances) - Static method in class org.processmining.pmind.algorithms.autocorrelations.CorrelationsCalculator
 
decisionActivityClasses - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
decisionMiner(UIPluginContext, Petrinet, XLog) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
decisionMiner(UIPluginContext, DataPetriNet, XLog) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
decisionMiner(UIPluginContext, PetrinetGraph, XLog) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
decisionMiner(UIPluginContext, Petrinet, XLog, PNRepResult) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
decisionMiner(UIPluginContext, DataPetriNet, XLog, PNRepResult) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
decisionMiner(UIPluginContext, PetrinetGraph, XLog, PNRepResult) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
DecisionMining - Class in org.processmining.datadiscovery.plugins
 
DecisionMining() - Constructor for class org.processmining.datadiscovery.plugins.DecisionMining
 
DecisionTreeFunctionEstimator - Class in org.processmining.datadiscovery.estimators.impl
 
DecisionTreeFunctionEstimator(Map<String, Type>, Map<String, Set<String>>, Object[], String, int) - Constructor for class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
Constructs a new DecisionTreeFunctionEstimator with the place's target transitions as CLASS value.
delete() - Method in class weka.core.Instances
Removes all instances from the set.
delete(int) - Method in class weka.core.Instances
Removes an instance at the given position from the set.
deleteAttributeAt(int) - Method in class weka.core.Instances
Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeType(int) - Method in class weka.core.Instances
Deletes all attributes of the given type in the dataset.
deleteStringAttributes() - Method in class weka.core.Instances
Deletes all string attributes in the dataset.
deleteWithMissing(int) - Method in class weka.core.Instances
Removes all instances with missing values for a particular attribute from the dataset.
deleteWithMissing(Attribute) - Method in class weka.core.Instances
Removes all instances with missing values for a particular attribute from the dataset.
deleteWithMissingClass() - Method in class weka.core.Instances
Removes all instances with a missing class value from the dataset.
DMNActivity - Class in org.processmining.pmind.models
 
DMNActivity(DMNModel, Activity) - Constructor for class org.processmining.pmind.models.DMNActivity
 
DMNActivityAttributePair - Class in org.processmining.pmind.models
 
DMNActivityAttributePair(Activity, DMNAttribute, Map<Integer, String>, int, double) - Constructor for class org.processmining.pmind.models.DMNActivityAttributePair
 
DMNAdminActivity - Class in org.processmining.pmind.models
 
DMNAdminActivity(DMNModel, Dot, Activity) - Constructor for class org.processmining.pmind.models.DMNAdminActivity
 
DMNAttribute - Class in org.processmining.pmind.models
 
DMNAttribute(String) - Constructor for class org.processmining.pmind.models.DMNAttribute
 
dmnAttributes - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
DMNDecisionActivity - Class in org.processmining.pmind.models
 
DMNDecisionActivity(DMNModel, Dot, Activity, DMNAttribute, int, Set<Integer>) - Constructor for class org.processmining.pmind.models.DMNDecisionActivity
 
DMNDecisionTable - Class in org.processmining.pmind.algorithms.concept
 
DMNDecisionTable() - Constructor for class org.processmining.pmind.algorithms.concept.DMNDecisionTable
 
DMNEdge - Class in org.processmining.pmind.models
 
DMNEdge(DMNNode, DMNNode, Integer, double, Dot) - Constructor for class org.processmining.pmind.models.DMNEdge
 
DMNInput - Class in org.processmining.pmind.models
 
DMNInput(DMNModel, Dot, DMNAttribute) - Constructor for class org.processmining.pmind.models.DMNInput
 
DMNKnowledgeNode - Class in org.processmining.pmind.models
 
DMNKnowledgeNode(DMNModel, Dot, DMNActivityAttributePair, String) - Constructor for class org.processmining.pmind.models.DMNKnowledgeNode
 
DMNMinerShiftBasedOld - Class in org.processmining.pmind.algorithms
 
DMNMinerShiftBasedOld(XLog, PMInDParameters) - Constructor for class org.processmining.pmind.algorithms.DMNMinerShiftBasedOld
 
DMNModel - Class in org.processmining.pmind.models
 
DMNModel(String, Set<Integer>, DMNActivityAttributePair) - Constructor for class org.processmining.pmind.models.DMNModel
 
DMNNode - Class in org.processmining.pmind.models
 
DMNNode(DMNModel) - Constructor for class org.processmining.pmind.models.DMNNode
 
doSubModels(DMNModel, Set<DMNModel>) - Method in class org.processmining.pmind.algorithms.PMInDModelChecker
 
dot - Variable in class org.processmining.pmind.models.DMNModel
 
doTheStuff(UIPluginContext, XLog, boolean, int) - Static method in class org.processmining.datadiscovery.QuickAndDirtyPlugin
 
dots - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 

E

edges - Variable in class org.processmining.pmind.models.DMNModel
 
eliminateDuplicates(Set<DMNModel>) - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
enumerateAttributes() - Method in class weka.core.Instances
Returns an enumeration of all the attributes.
enumerateInstances() - Method in class weka.core.Instances
Returns an enumeration of all instances in the dataset.
equalHeaders(Instances) - Method in class weka.core.Instances
Checks if two headers are equivalent.
equalHeadersMsg(Instances) - Method in class weka.core.Instances
Checks if two headers are equivalent.
equals(Object) - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
equals(Object) - Method in class org.processmining.pmind.algorithms.concept.TrainedModel
 
equals(Object) - Method in class org.processmining.pmind.models.DMNActivity
 
equals(Object) - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
equals(Object) - Method in class org.processmining.pmind.models.DMNAttribute
 
equals(Object) - Method in class org.processmining.pmind.models.DMNDecisionActivity
 
equals(Object) - Method in class org.processmining.pmind.models.DMNInput
 
equals(Object) - Method in class org.processmining.pmind.models.DMNKnowledgeNode
 
equals(Object) - Method in class org.processmining.pmind.models.DMNModel
 
equals(Object) - Method in class org.processmining.pmind.models.DMNNode
 
equals(Object) - Method in class weka.classifiers.evaluation.Evaluation
Tests whether the current evaluation object is equal to another evaluation object.
errorRate() - Method in class weka.classifiers.evaluation.Evaluation
Returns the estimated error rate or the root mean squared error (if the class is numeric).
evaluateModel(String, String[]) - Static method in class weka.classifiers.evaluation.Evaluation
Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, String[]) - Static method in class weka.classifiers.evaluation.Evaluation
Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, Instances, Object...) - Method in class weka.classifiers.evaluation.Evaluation
Evaluates the classifier on a given set of instances.
evaluateModelOnce(Classifier, Instance) - Method in class weka.classifiers.evaluation.Evaluation
Evaluates the classifier on a single instance.
evaluateModelOnce(double[], Instance) - Method in class weka.classifiers.evaluation.Evaluation
Evaluates the supplied distribution on a single instance.
evaluateModelOnce(double, Instance) - Method in class weka.classifiers.evaluation.Evaluation
Evaluates the supplied prediction on a single instance.
evaluateModelOnceAndRecordPrediction(Classifier, Instance) - Method in class weka.classifiers.evaluation.Evaluation
Evaluates the classifier on a single instance and records the prediction.
evaluateModelOnceAndRecordPrediction(double[], Instance) - Method in class weka.classifiers.evaluation.Evaluation
Evaluates the supplied distribution on a single instance.
Evaluation - Class in weka.classifiers.evaluation
Class for evaluating machine learning models.
Evaluation(Instances) - Constructor for class weka.classifiers.evaluation.Evaluation
Initializes all the counters for the evaluation.
Evaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.evaluation.Evaluation
Initializes all the counters for the evaluation and also takes a cost matrix as parameter.
evaluationForSingleInstance(double[], Instance, boolean) - Method in class weka.classifiers.evaluation.Evaluation
Evaluates the supplied distribution on a single instance.
evaluationForSingleInstance(Classifier, Instance, boolean) - Method in class weka.classifiers.evaluation.Evaluation
Evaluates the classifier on a single instance and records the prediction.
eventClassifier - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
EventLogOperations - Class in org.processmining.pmind.logs
 
EventLogOperations() - Constructor for class org.processmining.pmind.logs.EventLogOperations
 
expandDataset(DMNActivityAttributePair, Set<Integer>) - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
extractAttributeInformation(XLog) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
extractAttributeInformation(XLog, boolean) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 

F

falseNegativeRate(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculate the false negative rate with respect to a particular class.
falsePositiveRate(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculate the false positive rate with respect to a particular class.
FILE_EXTENSION - Static variable in class weka.core.Instances
The filename extension that should be used for arff files
findPossibleModels(DMNActivityAttributePair, Set<PossibleModel>, Collection<DMNActivityAttributePair>) - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
findRelatedNodes(int, DMNModel, AttributeShiftSequence, DMNActivityAttributePair, Set<Integer>) - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
findRelatedNodes(int, DMNModel, AttributeShiftSequence, DMNActivityAttributePair, Set<Integer>) - Method in class org.processmining.pmind.algorithms.DMNMinerShiftBasedOld
 
findRelatedNodes(int, DMNModel, AttributeShiftSequence, DMNActivityAttributePair, Set<Integer>) - Method in class org.processmining.pmind.algorithms.PMInDNoShifts
 
findRelatedNodes(int, DMNModel, AttributeShiftSequence, DMNActivityAttributePair, Set<Integer>) - Method in class org.processmining.pmind.algorithms.PMInDShiftBased
 
findRelatedNodes(int, DMNModel, AttributeShiftSequence, DMNActivityAttributePair, Set<Integer>) - Method in class org.processmining.pmind.algorithms.SOAPMInD
 
firstInstance() - Method in class weka.core.Instances
Returns the first instance in the set.
fixVarName(String) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
fMeasure(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculate the F-Measure with respect to a particular class.
foundStuff - Variable in class org.processmining.pmind.models.DMNModel
 

G

get(int) - Method in class weka.core.Instances
Returns the instance at the given position.
getAaPairs() - Method in class org.processmining.pmind.models.DMNModel
 
getAct() - Method in class org.processmining.pmind.algorithms.concept.TrainedModel
 
getActivities() - Method in class org.processmining.pmind.models.DMNModel
 
getActivity() - Method in class org.processmining.pmind.models.DMNActivity
 
getActivity() - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
getAllAppearancesBefore(int, int) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
getAllAppearancesBefore(XEventClass, int, int) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
getAllEvaluationMetricNames() - Static method in class weka.classifiers.evaluation.Evaluation
Utility method to get a list of the names of all built-in and plugin evaluation metrics
getAppearingTraces() - Method in class org.processmining.pmind.models.DMNAttribute
 
getASS() - Method in class org.processmining.pmind.models.DMNAttribute
 
getAt() - Method in class org.processmining.pmind.algorithms.concept.TrainedModel
 
getAttribute() - Method in class org.processmining.pmind.algorithms.concept.Shift
 
getAttribute() - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
getAttribute() - Method in class org.processmining.pmind.models.DMNDecisionActivity
 
getAttribute() - Method in class org.processmining.pmind.models.DMNInput
 
getAttributes() - Method in class org.processmining.pmind.algorithms.concept.ActivityDataStore
 
getAttributes() - Method in class org.processmining.pmind.models.Activity
 
getAttributes() - Method in class org.processmining.pmind.models.DMNModel
 
getAttributeValAtTracePos(DMNAttribute, int, int) - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
getClassifier() - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 
getClassifier() - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
getClassIndexMap() - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 
getClassPriors() - Method in class weka.classifiers.evaluation.Evaluation
Get the current weighted class counts.
getClassValue(Object) - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
Retrieve the classValue from 'mapping' for a given target class (Object)
getComparisons() - Method in class org.processmining.pmind.algorithms.PMInDModelChecker
 
getConnection(DMNDecisionActivity, DMNDecisionActivity) - Method in class org.processmining.pmind.models.DMNModel
 
getCorr() - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
getCorr() - Method in class org.processmining.pmind.models.DMNEdge
 
getCovered() - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getDAAPS() - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
getDepth(DMNActivityAttributePair, int) - Method in class org.processmining.pmind.models.DMNModel
 
getDepVar() - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
getDescription() - Method in class org.processmining.pmind.models.DMNKnowledgeNode
 
getDiscardPredictions() - Method in class weka.classifiers.evaluation.Evaluation
Returns whether predictions are not recorded at all, in order to conserve memory.
getDotEdge() - Method in class org.processmining.pmind.models.DMNEdge
 
getDotNode() - Method in class org.processmining.pmind.models.DMNNode
 
getEarliestAppearanceOf(XEventClass, int) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
getEarliestShiftOf(XEventClass, int) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
getEdges() - Method in class org.processmining.pmind.models.DMNModel
 
getEmptyClone() - Method in class org.processmining.pmind.models.DMNModel
 
getEventClass() - Method in class org.processmining.pmind.models.Activity
 
getEventType() - Method in class org.processmining.pmind.algorithms.concept.Shift
 
getFeatures() - Method in class org.processmining.pmind.algorithms.concept.DMNDecisionTable
 
getFeatures() - Method in class org.processmining.pmind.models.Activity
 
getFunctionEstimation(Object[]) - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
Returns a mapping from a Transition to a FunctionEstimation (i.e, a pair of (condition GuardExpression, and the likelihood of correct classification).
getGlobalInfo(Classifier) - Static method in class weka.classifiers.evaluation.Evaluation
Return the global info (if it exists) for the supplied classifier.
getGraph() - Method in class org.processmining.pmind.models.DMNNode
 
getHeader() - Method in class weka.classifiers.evaluation.Evaluation
Returns the header of the underlying dataset.
getIMSetting() - Method in class org.processmining.pmind.parameters.PMInDParameters
 
getInfo() - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
getInputAttributes() - Method in class org.processmining.pmind.models.Activity
 
getInputsOfDAAP(DMNActivityAttributePair) - Method in class org.processmining.pmind.models.DMNModel
 
getInstances() - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 
getKnowledgeNodes() - Method in class org.processmining.pmind.models.DMNModel
 
getLevels(ArrayList<String>) - Static method in class org.processmining.pmind.algorithms.autocorrelations.HelpFunctions
 
getLiteralValuesMap(XLog) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
getLiteralValuesMap(XLog, boolean) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
getLog() - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
getMatchedModel(DMNActivityAttributePair) - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getMetricsToDisplay() - Method in class weka.classifiers.evaluation.Evaluation
Get a list of the names of metrics to have appear in the output The default is to display all built in metrics and plugin metrics that haven't been globally disabled.
getMinCorrelation() - Method in class org.processmining.pmind.parameters.PMInDParameters
 
getMinDeviation() - Method in class org.processmining.pmind.parameters.PMInDParameters
 
getMiner() - Method in class org.processmining.pmind.output.PMInDOutput
 
getMinerType() - Method in class org.processmining.pmind.parameters.PMInDParameters
 
getMinSup() - Method in class org.processmining.pmind.parameters.PMInDParameters
 
getMinTraceProp() - Method in class org.processmining.pmind.parameters.PMInDParameters
 
getMissingEdgesM1() - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getMissingEdgesM2() - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getMissingInM() - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getMissingInM2() - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getModel1() - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getModel2() - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getModels() - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
getModels() - Method in class org.processmining.pmind.algorithms.concept.TraceCluster
 
getModels() - Method in class org.processmining.pmind.output.PMInDOutput
 
getName() - Method in class org.processmining.pmind.models.Activity
 
getNode(DMNActivityAttributePair) - Method in class org.processmining.pmind.models.DMNModel
 
getNodes() - Method in class org.processmining.pmind.models.Activity
 
getNodes() - Method in class org.processmining.pmind.models.DMNModel
 
getNthAppearanceOf(XEventClass, int, int) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
getNthShifts(DMNAttribute, int) - Method in class org.processmining.pmind.models.Activity
 
getOrderedShiftsOfTrace(int) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
getOrderedShiftsOfTraceBefore(int, int) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
getOuput1() - Method in class org.processmining.pmind.output.PMInDConformanceOutput
 
getOuput2() - Method in class org.processmining.pmind.output.PMInDConformanceOutput
 
getOutcome() - Method in class org.processmining.pmind.algorithms.concept.PredictiveModel
 
getOutputDependencies() - Method in class org.processmining.pmind.models.DMNAttribute
 
getParameters() - Method in class org.processmining.pmind.output.PMInDOutput
 
getParameters() - Method in class org.processmining.pmind.parameters.PMInDSettingsDialog
 
getPetriNet() - Method in class org.processmining.pmind.algorithms.concept.TraceCluster
 
getPetrinet() - Method in class org.processmining.pmind.models.DMNModel
 
getPluginMetric(String) - Method in class weka.classifiers.evaluation.Evaluation
Get the named plugin evaluation metric
getPluginMetrics() - Method in class weka.classifiers.evaluation.Evaluation
Returns the list of plugin metrics in use (or null if there are none)
getPosition() - Method in class org.processmining.pmind.algorithms.concept.Shift
 
getPredModel() - Method in class org.processmining.pmind.algorithms.concept.PredictiveModel
 
getRandomNumberGenerator(long) - Method in class weka.core.Instances
Returns a random number generator.
getReplayResult(DMNActivityAttributePair) - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getReplayResults() - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getRevision() - Method in class weka.classifiers.evaluation.Evaluation
Returns the revision string.
getRevision() - Method in class weka.core.Instances
Returns the revision string.
getScore() - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getSettedAttributes() - Method in class org.processmining.pmind.models.Activity
 
getShift() - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
getShift() - Method in class org.processmining.pmind.models.DMNDecisionActivity
 
getShiftingAttributes(double) - Method in class org.processmining.pmind.models.Activity
 
getShiftingTracesForCardinality(int) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
getShiftingTracesPerCardinality(int) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
getShiftRatio() - Method in class org.processmining.pmind.parameters.PMInDParameters
 
getShifts(DMNAttribute, Integer) - Method in class org.processmining.pmind.models.Activity
 
getShifts(DMNAttribute) - Method in class org.processmining.pmind.models.Activity
 
getShiftsOfTrace(int) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
getShiftTraces(DMNAttribute) - Method in class org.processmining.pmind.models.Activity
 
getSingleDAAPS() - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
getSubModels() - Method in class org.processmining.pmind.algorithms.concept.ModelComparison
 
getSubModels() - Method in class org.processmining.pmind.models.DMNModel
 
getSup() - Method in class org.processmining.pmind.algorithms.concept.TrainedModel
 
getSuperModel() - Method in class org.processmining.pmind.models.DMNModel
 
getTopActivity() - Method in class org.processmining.pmind.models.DMNModel
 
getTopActivityNode() - Method in class org.processmining.pmind.models.DMNModel
 
getTopDAAP() - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
getTopModels() - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
getTraceClusters() - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
getTraceClusters() - Method in class org.processmining.pmind.output.PMInDOutput
 
getTraceNo() - Method in class org.processmining.pmind.algorithms.concept.Shift
 
getTraces() - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
getTraces() - Method in class org.processmining.pmind.algorithms.concept.TraceCluster
 
getTraces() - Method in class org.processmining.pmind.algorithms.concept.TrainedModel
 
getTraces() - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
getTraces() - Method in class org.processmining.pmind.models.DMNAttribute
 
getTraces() - Method in class org.processmining.pmind.models.DMNDecisionActivity
 
getTraces() - Method in class org.processmining.pmind.models.DMNModel
 
getTrainedModels() - Method in class org.processmining.pmind.models.DMNModel
 
getUnmatchedModels() - Method in class org.processmining.pmind.algorithms.PMInDModelChecker
 
getValueForAt(DMNAttribute, int) - Method in class org.processmining.pmind.algorithms.concept.ActivityDataStore
 
getValueInTrace(int) - Method in class org.processmining.pmind.models.DMNAttribute
 
getValueOfTrace(int) - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
getValues() - Method in class org.processmining.pmind.models.DMNAttribute
 
getWeight() - Method in class org.processmining.pmind.models.DMNEdge
 

H

handleCostOption(String, int) - Static method in class weka.classifiers.evaluation.Evaluation
Attempts to load a cost matrix.
hasSameActivitySequence(AttributeShiftSequence, int) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
HelpFunctions - Class in org.processmining.pmind.algorithms.autocorrelations
 
HelpFunctions() - Constructor for class org.processmining.pmind.algorithms.autocorrelations.HelpFunctions
 

I

im - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
incorrect() - Method in class weka.classifiers.evaluation.Evaluation
Gets the number of instances incorrectly classified (that is, for which an incorrect prediction was made).
initialize(Instances, int) - Method in class weka.core.Instances
initializes with the header information of the given dataset and sets the capacity of the set of instances.
insertAttributeAt(Attribute, int) - Method in class weka.core.Instances
Inserts an attribute at the given position (0 to numAttributes()) and sets all values to be missing.
instance(int) - Method in class weka.core.Instances
Returns the instance at the given position.
Instances - Class in weka.core
Class for handling an ordered set of weighted instances.
Instances(Reader) - Constructor for class weka.core.Instances
Reads an ARFF file from a reader, and assigns a weight of one to each instance.
Instances(Reader, int) - Constructor for class weka.core.Instances
Deprecated.
instead of using this method in conjunction with the readInstance(Reader) method, one should use the ArffLoader or DataSource class instead.
Instances(Instances) - Constructor for class weka.core.Instances
Constructor copying all instances and references to the header information from the given set of instances.
Instances(Instances, int) - Constructor for class weka.core.Instances
Constructor creating an empty set of instances.
Instances(Instances, int, int) - Constructor for class weka.core.Instances
Creates a new set of instances by copying a subset of another set.
Instances(String, ArrayList<Attribute>, int) - Constructor for class weka.core.Instances
Creates an empty set of instances.
instancesAndWeights() - Method in class weka.core.Instances
Returns string including all instances, their weights and their indices in the original dataset.
isBefore(XEventClass, XEventClass) - Method in class org.processmining.pmind.algorithms.concept.AttributeShiftSequence
 
isModelBased() - Method in class org.processmining.pmind.parameters.PMInDParameters
 
isPerTrace() - Method in class org.processmining.pmind.output.PMInDOutput
 
isPrintModels() - Method in class org.processmining.pmind.parameters.PMInDParameters
 
isTreatNoLeafAsFalse() - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 

K

k_MarginResolution - Static variable in class weka.classifiers.evaluation.Evaluation
Resolution of the margin histogram.
kappa() - Method in class weka.classifiers.evaluation.Evaluation
Returns value of kappa statistic if class is nominal.
KBInformation() - Method in class weka.classifiers.evaluation.Evaluation
Return the total Kononenko & Bratko Information score in bits.
KBMeanInformation() - Method in class weka.classifiers.evaluation.Evaluation
Return the Kononenko & Bratko Information score in bits per instance.
KBRelativeInformation() - Method in class weka.classifiers.evaluation.Evaluation
Return the Kononenko & Bratko Relative Information score.
knowledgeNodes - Variable in class org.processmining.pmind.models.DMNModel
 
kthSmallestValue(Attribute, int) - Method in class weka.core.Instances
Returns the kth-smallest attribute value of a numeric attribute.
kthSmallestValue(int, int) - Method in class weka.core.Instances
Returns the kth-smallest attribute value of a numeric attribute.

L

lastInstance() - Method in class weka.core.Instances
Returns the last instance in the set.
loadEventLog(String) - Static method in class org.processmining.pmind.logs.EventLogOperations
 
log - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 

M

m_Attributes - Variable in class weka.core.Instances
The attribute information.
m_ClassIndex - Variable in class weka.core.Instances
The class attribute's index
m_ClassIsNominal - Variable in class weka.classifiers.evaluation.Evaluation
Is the class nominal or numeric?
m_ClassNames - Variable in class weka.classifiers.evaluation.Evaluation
The names of the classes.
m_ClassPriors - Variable in class weka.classifiers.evaluation.Evaluation
The prior probabilities of the classes.
m_ClassPriorsSum - Variable in class weka.classifiers.evaluation.Evaluation
The sum of counts for priors.
m_ComplexityStatisticsAvailable - Variable in class weka.classifiers.evaluation.Evaluation
Whether complexity statistics are available.
m_ConfLevel - Variable in class weka.classifiers.evaluation.Evaluation
The confidence level used for coverage statistics.
m_ConfusionMatrix - Variable in class weka.classifiers.evaluation.Evaluation
Array for storing the confusion matrix.
m_Correct - Variable in class weka.classifiers.evaluation.Evaluation
The weight of all correctly classified instances.
m_CostMatrix - Variable in class weka.classifiers.evaluation.Evaluation
The cost matrix (if given).
m_CoverageStatisticsAvailable - Variable in class weka.classifiers.evaluation.Evaluation
Whether coverage statistics are available.
m_DiscardPredictions - Variable in class weka.classifiers.evaluation.Evaluation
whether to discard predictions (and save memory).
m_Header - Variable in class weka.classifiers.evaluation.Evaluation
The header of the training set.
m_Incorrect - Variable in class weka.classifiers.evaluation.Evaluation
The weight of all incorrectly classified instances.
m_Instances - Variable in class weka.core.Instances
The instances.
m_Lines - Variable in class weka.core.Instances
The lines read so far in case of incremental loading.
m_MarginCounts - Variable in class weka.classifiers.evaluation.Evaluation
Cumulative margin distribution.
m_MaxTarget - Variable in class weka.classifiers.evaluation.Evaluation
Maximum target value.
m_metricsToDisplay - Variable in class weka.classifiers.evaluation.Evaluation
The list of metrics to display in the output
m_MinTarget - Variable in class weka.classifiers.evaluation.Evaluation
Minimum target value.
m_MissingClass - Variable in class weka.classifiers.evaluation.Evaluation
The weight of all instances that had no class assigned to them.
m_NamesToAttributeIndices - Variable in class weka.core.Instances
A map to quickly find attribute indices based on their names.
m_NoPriors - Variable in class weka.classifiers.evaluation.Evaluation
enables/disables the use of priors, e.g., if no training set is present in case of de-serialized schemes.
m_NumClasses - Variable in class weka.classifiers.evaluation.Evaluation
The number of classes.
m_NumFolds - Variable in class weka.classifiers.evaluation.Evaluation
The number of folds for a cross-validation.
m_NumTrainClassVals - Variable in class weka.classifiers.evaluation.Evaluation
Number of non-missing class training instances seen.
m_pluginMetrics - Variable in class weka.classifiers.evaluation.Evaluation
Holds plugin evaluation metrics
m_Predictions - Variable in class weka.classifiers.evaluation.Evaluation
The list of predictions that have been generated (for computing AUC).
m_PriorEstimator - Variable in class weka.classifiers.evaluation.Evaluation
Numeric class estimator for prior.
m_RelationName - Variable in class weka.core.Instances
The dataset's name.
m_SumAbsErr - Variable in class weka.classifiers.evaluation.Evaluation
Sum of absolute errors.
m_SumClass - Variable in class weka.classifiers.evaluation.Evaluation
Sum of class values.
m_SumClassPredicted - Variable in class weka.classifiers.evaluation.Evaluation
Sum of predicted * class values.
m_SumErr - Variable in class weka.classifiers.evaluation.Evaluation
Sum of errors.
m_SumKBInfo - Variable in class weka.classifiers.evaluation.Evaluation
Total Kononenko & Bratko Information.
m_SumPredicted - Variable in class weka.classifiers.evaluation.Evaluation
Sum of predicted values.
m_SumPriorAbsErr - Variable in class weka.classifiers.evaluation.Evaluation
Sum of absolute errors of the prior.
m_SumPriorEntropy - Variable in class weka.classifiers.evaluation.Evaluation
Total entropy of prior predictions.
m_SumPriorSqrErr - Variable in class weka.classifiers.evaluation.Evaluation
Sum of absolute errors of the prior.
m_SumSchemeEntropy - Variable in class weka.classifiers.evaluation.Evaluation
Total entropy of scheme predictions.
m_SumSqrClass - Variable in class weka.classifiers.evaluation.Evaluation
Sum of squared class values.
m_SumSqrErr - Variable in class weka.classifiers.evaluation.Evaluation
Sum of squared errors.
m_SumSqrPredicted - Variable in class weka.classifiers.evaluation.Evaluation
Sum of squared predicted values.
m_TotalCost - Variable in class weka.classifiers.evaluation.Evaluation
The total cost of predictions (includes instance weights).
m_TotalCoverage - Variable in class weka.classifiers.evaluation.Evaluation
Total coverage of test cases at the given confidence level.
m_TotalSizeOfRegions - Variable in class weka.classifiers.evaluation.Evaluation
Total size of predicted regions at the given confidence level.
m_TrainClassVals - Variable in class weka.classifiers.evaluation.Evaluation
Array containing all numeric training class values seen.
m_TrainClassWeights - Variable in class weka.classifiers.evaluation.Evaluation
Array containing all numeric training class weights.
m_Unclassified - Variable in class weka.classifiers.evaluation.Evaluation
The weight of all unclassified instances.
m_WithClass - Variable in class weka.classifiers.evaluation.Evaluation
The weight of all instances that had a class assigned to them.
main(String[]) - Static method in class org.processmining.pmind.plugins.ConstructCorrelationsForEventAttributes
 
main(String[]) - Static method in class org.processmining.pmind.plugins.PMInDStandalone
 
main(String[]) - Static method in class org.processmining.pmind.plugins.PMInDStandaloneBenchmark
 
main(String[]) - Static method in class weka.classifiers.evaluation.Evaluation
A test method for this class.
main(String[]) - Static method in class weka.core.Instances
Main method for this class.
mainAtt - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
mainModel - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
makeDistribution(double) - Method in class weka.classifiers.evaluation.Evaluation
Convert a single prediction into a probability distribution with all zero probabilities except the predicted value which has probability 1.0.
makeOptionString(Classifier, boolean) - Static method in class weka.classifiers.evaluation.Evaluation
Make up the help string giving all the command line options.
matthewsCorrelationCoefficient(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculates the matthews correlation coefficient (sometimes called phi coefficient) for the supplied class
meanAbsoluteError() - Method in class weka.classifiers.evaluation.Evaluation
Returns the mean absolute error.
meanOrMode(int) - Method in class weka.core.Instances
Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.
meanOrMode(Attribute) - Method in class weka.core.Instances
Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.
meanPriorAbsoluteError() - Method in class weka.classifiers.evaluation.Evaluation
Returns the mean absolute error of the prior.
mergeInstances(Instances, Instances) - Static method in class weka.core.Instances
Merges two sets of Instances together.
MIN_SF_PROB - Static variable in class weka.classifiers.evaluation.Evaluation
The minimum probablility accepted from an estimator to avoid taking log(0) in Sf calculations.
minCorr - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
minDev - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
mineDMNModels() - Method in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
minSup - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
minTrace - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
minTraceProportion - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
modelBased - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
ModelComparison - Class in org.processmining.pmind.algorithms.concept
 
ModelComparison(DMNModel, DMNModel, Map<DMNActivityAttributePair, DMNActivityAttributePair>, Set<DMNActivityAttributePair>, Set<DMNActivityAttributePair>, Set<DMNEdge>, Set<DMNEdge>, double) - Constructor for class org.processmining.pmind.algorithms.concept.ModelComparison
 
modelPrint - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
models - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 

N

node - Variable in class org.processmining.pmind.models.DMNNode
 
nodes - Variable in class org.processmining.pmind.models.DMNModel
 
num2ShortID(int, char[], int) - Method in class weka.classifiers.evaluation.Evaluation
Method for generating indices for the confusion matrix.
numAttributes() - Method in class weka.core.Instances
Returns the number of attributes.
numClasses() - Method in class weka.core.Instances
Returns the number of class labels.
numDistinctValues(int) - Method in class weka.core.Instances
Returns the number of distinct values of a given attribute.
numDistinctValues(Attribute) - Method in class weka.core.Instances
Returns the number of distinct values of a given attribute.
numFalseNegatives(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculate number of false negatives with respect to a particular class.
numFalsePositives(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculate number of false positives with respect to a particular class.
numInstances() - Method in class weka.classifiers.evaluation.Evaluation
Gets the number of test instances that had a known class value (actually the sum of the weights of test instances with known class value).
numInstances() - Method in class weka.core.Instances
Returns the number of instances in the dataset.
numTrueNegatives(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculate the number of true negatives with respect to a particular class.
numTruePositives(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculate the number of true positives with respect to a particular class.

O

org.processmining.datadiscovery - package org.processmining.datadiscovery
 
org.processmining.datadiscovery.estimators.impl - package org.processmining.datadiscovery.estimators.impl
 
org.processmining.datadiscovery.plugins - package org.processmining.datadiscovery.plugins
 
org.processmining.pmind.algorithms - package org.processmining.pmind.algorithms
 
org.processmining.pmind.algorithms.autocorrelations - package org.processmining.pmind.algorithms.autocorrelations
 
org.processmining.pmind.algorithms.concept - package org.processmining.pmind.algorithms.concept
 
org.processmining.pmind.help - package org.processmining.pmind.help
 
org.processmining.pmind.logs - package org.processmining.pmind.logs
 
org.processmining.pmind.models - package org.processmining.pmind.models
 
org.processmining.pmind.output - package org.processmining.pmind.output
 
org.processmining.pmind.parameters - package org.processmining.pmind.parameters
 
org.processmining.pmind.plugins - package org.processmining.pmind.plugins
 
outputClasses - Variable in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 

P

pctCorrect() - Method in class weka.classifiers.evaluation.Evaluation
Gets the percentage of instances correctly classified (that is, for which a correct prediction was made).
pctIncorrect() - Method in class weka.classifiers.evaluation.Evaluation
Gets the percentage of instances incorrectly classified (that is, for which an incorrect prediction was made).
pctUnclassified() - Method in class weka.classifiers.evaluation.Evaluation
Gets the percentage of instances not classified (that is, for which no prediction was made by the classifier).
petrinet - Variable in class org.processmining.pmind.models.DMNModel
 
plugin(UIPluginContext, PetrinetGraph, XLog, boolean) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
The method that performs the actual mining to discover the process data-flow on decision points.
PMInDCheckerVisualizer - Class in org.processmining.pmind.plugins
 
PMInDCheckerVisualizer() - Constructor for class org.processmining.pmind.plugins.PMInDCheckerVisualizer
 
PMInDConformanceOutput - Class in org.processmining.pmind.output
 
PMInDConformanceOutput(AbstractDMNMiner, AbstractDMNMiner) - Constructor for class org.processmining.pmind.output.PMInDConformanceOutput
 
PMInDConformancePlugin - Class in org.processmining.pmind.plugins
 
PMInDConformancePlugin() - Constructor for class org.processmining.pmind.plugins.PMInDConformancePlugin
 
PMInDConformancePreloaded - Class in org.processmining.pmind.plugins
 
PMInDConformancePreloaded() - Constructor for class org.processmining.pmind.plugins.PMInDConformancePreloaded
 
PMInDHelp - Class in org.processmining.pmind.help
 
PMInDHelp() - Constructor for class org.processmining.pmind.help.PMInDHelp
 
PMInDModelChecker - Class in org.processmining.pmind.algorithms
 
PMInDModelChecker(PMInDConformanceOutput) - Constructor for class org.processmining.pmind.algorithms.PMInDModelChecker
 
PMInDNoShifts - Class in org.processmining.pmind.algorithms
 
PMInDNoShifts(XLog, PMInDParameters) - Constructor for class org.processmining.pmind.algorithms.PMInDNoShifts
 
PMInDOutput - Class in org.processmining.pmind.output
 
PMInDOutput(AbstractDMNMiner, PMInDParameters) - Constructor for class org.processmining.pmind.output.PMInDOutput
 
PMInDOutputVisualizer - Class in org.processmining.pmind.plugins
 
PMInDOutputVisualizer() - Constructor for class org.processmining.pmind.plugins.PMInDOutputVisualizer
 
PMInDParameters - Class in org.processmining.pmind.parameters
 
PMInDParameters() - Constructor for class org.processmining.pmind.parameters.PMInDParameters
 
PMInDParameters.MinerType - Enum in org.processmining.pmind.parameters
 
PMInDProMPlugin - Class in org.processmining.pmind.plugins
 
PMInDProMPlugin() - Constructor for class org.processmining.pmind.plugins.PMInDProMPlugin
 
PMInDProMPluginPreloaded - Class in org.processmining.pmind.plugins
 
PMInDProMPluginPreloaded() - Constructor for class org.processmining.pmind.plugins.PMInDProMPluginPreloaded
 
PMInDSettingsDialog - Class in org.processmining.pmind.parameters
 
PMInDSettingsDialog(UIPluginContext) - Constructor for class org.processmining.pmind.parameters.PMInDSettingsDialog
 
PMInDShiftBased - Class in org.processmining.pmind.algorithms
 
PMInDShiftBased(XLog, PMInDParameters) - Constructor for class org.processmining.pmind.algorithms.PMInDShiftBased
 
PMInDStandalone - Class in org.processmining.pmind.plugins
 
PMInDStandalone() - Constructor for class org.processmining.pmind.plugins.PMInDStandalone
 
PMInDStandaloneBenchmark - Class in org.processmining.pmind.plugins
 
PMInDStandaloneBenchmark() - Constructor for class org.processmining.pmind.plugins.PMInDStandaloneBenchmark
 
PossibleModel - Class in org.processmining.pmind.algorithms.concept
 
PossibleModel(Set<DMNActivityAttributePair>, DMNActivityAttributePair, Set<Integer>) - Constructor for class org.processmining.pmind.algorithms.concept.PossibleModel
 
PossibleModel(DMNActivityAttributePair, DMNActivityAttributePair, Set<Integer>) - Constructor for class org.processmining.pmind.algorithms.concept.PossibleModel
 
precision(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculate the precision with respect to a particular class.
predictions() - Method in class weka.classifiers.evaluation.Evaluation
Returns the predictions that have been collected.
PredictiveModel - Class in org.processmining.pmind.algorithms.concept
 
PredictiveModel(Classifier, double) - Constructor for class org.processmining.pmind.algorithms.concept.PredictiveModel
 
printActivitiesPerAttribute() - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
printDependencies() - Method in class org.processmining.pmind.models.Activity
 
printInstances() - Method in class org.processmining.pmind.models.Activity
 
printShifts() - Method in class org.processmining.pmind.models.Activity
 
priorEntropy() - Method in class weka.classifiers.evaluation.Evaluation
Calculate the entropy of the prior distribution.

Q

QuickAndDirtyPlugin - Class in org.processmining.datadiscovery
 
QuickAndDirtyPlugin() - Constructor for class org.processmining.datadiscovery.QuickAndDirtyPlugin
 

R

randomize(Random) - Method in class weka.core.Instances
Shuffles the instances in the set so that they are ordered randomly.
readInstance(Reader) - Method in class weka.core.Instances
Deprecated.
instead of using this method in conjunction with the readInstance(Reader) method, one should use the ArffLoader or DataSource class instead.
recall(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculate the recall with respect to a particular class.
recursivelyGetSubModels() - Method in class org.processmining.pmind.models.DMNModel
 
relationName() - Method in class weka.core.Instances
Returns the relation's name.
relativeAbsoluteError() - Method in class weka.classifiers.evaluation.Evaluation
Returns the relative absolute error.
remove(int) - Method in class weka.core.Instances
Removes the instance at the given position.
removeEdge(DirectedGraphEdge) - Method in class org.processmining.pmind.models.DMNModel
 
removeNode(DirectedGraphNode) - Method in class org.processmining.pmind.models.DMNModel
 
renameAttribute(int, String) - Method in class weka.core.Instances
Renames an attribute.
renameAttribute(Attribute, String) - Method in class weka.core.Instances
Renames an attribute.
renameAttributeValue(int, int, String) - Method in class weka.core.Instances
Renames the value of a nominal (or string) attribute value.
renameAttributeValue(Attribute, String, String) - Method in class weka.core.Instances
Renames the value of a nominal (or string) attribute value.
replaceAttributeAt(Attribute, int) - Method in class weka.core.Instances
Replaces the attribute at the given position (0 to numAttributes()) with the given attribute and sets all its values to be missing.
replaceNonUriEncodedChars(String) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
resample(Random) - Method in class weka.core.Instances
Creates a new dataset of the same size using random sampling with replacement.
resampleWithWeights(Random) - Method in class weka.core.Instances
Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.
resampleWithWeights(Random, boolean[]) - Method in class weka.core.Instances
Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.
resampleWithWeights(Random, boolean) - Method in class weka.core.Instances
Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.
resampleWithWeights(Random, boolean[], boolean) - Method in class weka.core.Instances
Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.
resampleWithWeights(Random, double[]) - Method in class weka.core.Instances
Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.
resampleWithWeights(Random, double[], boolean[]) - Method in class weka.core.Instances
Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.
resampleWithWeights(Random, double[], boolean[], boolean) - Method in class weka.core.Instances
Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.
rootMeanPriorSquaredError() - Method in class weka.classifiers.evaluation.Evaluation
Returns the root mean prior squared error.
rootMeanSquaredError() - Method in class weka.classifiers.evaluation.Evaluation
Returns the root mean squared error.
rootRelativeSquaredError() - Method in class weka.classifiers.evaluation.Evaluation
Returns the root relative squared error if the class is numeric.
run(UIPluginContext) - Method in class org.processmining.datadiscovery.QuickAndDirtyPlugin
 
run(UIPluginContext, PMInDModelChecker) - Method in class org.processmining.pmind.plugins.PMInDCheckerVisualizer
 
run(UIPluginContext, PMInDOutput, XLog) - Method in class org.processmining.pmind.plugins.PMInDConformancePlugin
 
run(UIPluginContext) - Method in class org.processmining.pmind.plugins.PMInDConformancePreloaded
 
run(UIPluginContext, PMInDOutput) - Method in class org.processmining.pmind.plugins.PMInDOutputVisualizer
 
run(UIPluginContext, XLog) - Method in class org.processmining.pmind.plugins.PMInDProMPlugin
 
run(UIPluginContext) - Method in class org.processmining.pmind.plugins.PMInDProMPluginPreloaded
 

S

searchForAutocorrelations() - Method in class org.processmining.pmind.algorithms.autocorrelations.CorrelationsCalculator
 
SERIALIZED_OBJ_FILE_EXTENSION - Static variable in class weka.core.Instances
The filename extension that should be used for bin.
set(int, Instance) - Method in class weka.core.Instances
Replaces the instance at the given position.
setActivity(Activity) - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
setAttribute(DMNAttribute) - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
setAttribute(DMNAttribute) - Method in class org.processmining.pmind.models.DMNDecisionActivity
 
setClass(Attribute) - Method in class weka.core.Instances
Sets the class attribute.
setClassifier(Classifier) - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
setClassIndex(int) - Method in class weka.core.Instances
Sets the class index of the set.
setCorr(double) - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
setDescription(String) - Method in class org.processmining.pmind.models.DMNKnowledgeNode
 
setDiscardPredictions(boolean) - Method in class weka.classifiers.evaluation.Evaluation
Sets whether to discard predictions, ie, not storing them for future reference via predictions() method in order to conserve memory.
setIMSetting(Integer) - Method in class org.processmining.pmind.parameters.PMInDParameters
 
setLabel(String) - Method in class org.processmining.pmind.models.DMNModel
 
setMetricsToDisplay(List<String>) - Method in class weka.classifiers.evaluation.Evaluation
Set a list of the names of metrics to have appear in the output.
setMinCorrelation(Integer) - Method in class org.processmining.pmind.parameters.PMInDParameters
 
setMinDeviation(Integer) - Method in class org.processmining.pmind.parameters.PMInDParameters
 
setMinerType(PMInDParameters.MinerType) - Method in class org.processmining.pmind.parameters.PMInDParameters
 
setMinSup(Integer) - Method in class org.processmining.pmind.parameters.PMInDParameters
 
setMinTraceProp(Integer) - Method in class org.processmining.pmind.parameters.PMInDParameters
 
setModelBased(boolean) - Method in class org.processmining.pmind.parameters.PMInDParameters
 
setNumericPriorsFromBuffer() - Method in class weka.classifiers.evaluation.Evaluation
Sets up the priors for numeric class attributes from the training class values that have been seen so far.
setOutcome(double) - Method in class org.processmining.pmind.algorithms.concept.PredictiveModel
 
setPredModel(Classifier) - Method in class org.processmining.pmind.algorithms.concept.PredictiveModel
 
setPrintModels(boolean) - Method in class org.processmining.pmind.parameters.PMInDParameters
 
setPriors(Instances) - Method in class weka.classifiers.evaluation.Evaluation
Sets the class prior probabilities.
setRelationName(String) - Method in class weka.core.Instances
Sets the relation's name.
setShift(int) - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
setShift(int) - Method in class org.processmining.pmind.models.DMNDecisionActivity
 
setShiftRatio(Integer) - Method in class org.processmining.pmind.parameters.PMInDParameters
 
setSup(double) - Method in class org.processmining.pmind.algorithms.concept.TrainedModel
 
setSuperModel(DMNModel) - Method in class org.processmining.pmind.models.DMNModel
 
setTopActivity(DMNActivityAttributePair) - Method in class org.processmining.pmind.models.DMNModel
 
setTopDAAP(DMNActivityAttributePair) - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
setTraces(Set<Integer>) - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
setTraces(Set<Integer>) - Method in class org.processmining.pmind.models.DMNDecisionActivity
 
setTreatNoLeafAsFalse(boolean) - Method in class org.processmining.datadiscovery.estimators.impl.DecisionTreeFunctionEstimator
 
SFEntropyGain() - Method in class weka.classifiers.evaluation.Evaluation
Returns the total SF, which is the null model entropy minus the scheme entropy.
SFMeanEntropyGain() - Method in class weka.classifiers.evaluation.Evaluation
Returns the SF per instance, which is the null model entropy minus the scheme entropy, per instance.
SFMeanPriorEntropy() - Method in class weka.classifiers.evaluation.Evaluation
Returns the entropy per instance for the null model.
SFMeanSchemeEntropy() - Method in class weka.classifiers.evaluation.Evaluation
Returns the entropy per instance for the scheme.
SFPriorEntropy() - Method in class weka.classifiers.evaluation.Evaluation
Returns the total entropy for the null model.
SFSchemeEntropy() - Method in class weka.classifiers.evaluation.Evaluation
Returns the total entropy for the scheme.
Shift - Class in org.processmining.pmind.algorithms.concept
 
Shift(XEventClass, DMNAttribute, int, int) - Constructor for class org.processmining.pmind.algorithms.concept.Shift
 
shiftRatio - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
size() - Method in class weka.core.Instances
Returns the number of instances in the dataset.
sizeOfPredictedRegions() - Method in class weka.classifiers.evaluation.Evaluation
Gets the average size of the predicted regions, relative to the range of the target in the training data, at the confidence level specified when evaluation was performed.
SOAPMInD - Class in org.processmining.pmind.algorithms
 
SOAPMInD(XLog, PMInDParameters) - Constructor for class org.processmining.pmind.algorithms.SOAPMInD
 
sort(int) - Method in class weka.core.Instances
Sorts the instances based on an attribute.
sort(Attribute) - Method in class weka.core.Instances
Sorts the instances based on an attribute.
sortBasedOnNominalAttribute(int) - Method in class weka.core.Instances
Sorts a nominal attribute (stable, linear-time sort).
stableSort(int) - Method in class weka.core.Instances
Sorts the instances based on an attribute, using a stable sort.
stableSort(Attribute) - Method in class weka.core.Instances
Sorts the instances based on an attribute, using a stable sort.
stratify(int) - Method in class weka.core.Instances
Stratifies a set of instances according to its class values if the class attribute is nominal (so that afterwards a stratified cross-validation can be performed).
stratStep(int) - Method in class weka.core.Instances
Help function needed for stratification of set.
stringFreeStructure() - Method in class weka.core.Instances
Create a copy of the structure.
stringWithoutHeader() - Method in class weka.core.Instances
Returns the instances in the dataset as a string in ARFF format.
submodels - Variable in class org.processmining.pmind.models.DMNModel
 
sumOfWeights() - Method in class weka.core.Instances
Computes the sum of all the instances' weights.
superModel - Variable in class org.processmining.pmind.models.DMNModel
 
swap(int, int) - Method in class weka.core.Instances
Swaps two instances in the set.

T

test(String[]) - Static method in class weka.core.Instances
Method for testing this class.
testCV(int, int) - Method in class weka.core.Instances
Creates the test set for one fold of a cross-validation on the dataset.
testDistinctValues(int) - Method in class weka.core.Instances
 
TEXT - Static variable in class org.processmining.pmind.help.PMInDHelp
 
toClassDetailsString() - Method in class weka.classifiers.evaluation.Evaluation
Generates a breakdown of the accuracy for each class (with default title), incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toClassDetailsString(String) - Method in class weka.classifiers.evaluation.Evaluation
Generates a breakdown of the accuracy for each class, incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toCumulativeMarginDistributionString() - Method in class weka.classifiers.evaluation.Evaluation
Output the cumulative margin distribution as a string suitable for input for gnuplot or similar package.
toDot() - Method in class org.processmining.pmind.models.DMNModel
 
toDotString() - Method in class org.processmining.pmind.models.DMNAttribute
 
toggleEvalMetrics(List<String>) - Method in class weka.classifiers.evaluation.Evaluation
Toggle the output of the metrics specified in the supplied list.
toMatrixString() - Method in class weka.classifiers.evaluation.Evaluation
Calls toMatrixString() with a default title.
toMatrixString(String) - Method in class weka.classifiers.evaluation.Evaluation
Outputs the performance statistics as a classification confusion matrix.
topActivity - Variable in class org.processmining.pmind.models.DMNModel
 
topModels - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
toString() - Method in class org.processmining.pmind.algorithms.concept.PossibleModel
 
toString() - Method in class org.processmining.pmind.models.Activity
 
toString() - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
toString() - Method in class org.processmining.pmind.models.DMNAttribute
 
toString() - Method in enum org.processmining.pmind.parameters.PMInDParameters.MinerType
 
toString() - Method in class org.processmining.pmind.parameters.PMInDParameters
 
toString() - Method in class weka.core.Instances
Returns the dataset as a string in ARFF format.
toSummaryString() - Method in class weka.classifiers.evaluation.Evaluation
Calls toSummaryString() with no title and no complexity stats.
toSummaryString(boolean) - Method in class weka.classifiers.evaluation.Evaluation
Calls toSummaryString() with a default title.
toSummaryString(String, boolean) - Method in class weka.classifiers.evaluation.Evaluation
Outputs the performance statistics in summary form.
toSummaryString() - Method in class weka.core.Instances
Generates a string summarizing the set of instances.
totalCost() - Method in class weka.classifiers.evaluation.Evaluation
Gets the total cost, that is, the cost of each prediction times the weight of the instance, summed over all instances.
toVerboseString() - Method in class org.processmining.pmind.models.DMNAttribute
 
TraceCluster - Class in org.processmining.pmind.algorithms.concept
 
TraceCluster(Collection<DMNModel>, Collection<Integer>, Object[]) - Constructor for class org.processmining.pmind.algorithms.concept.TraceCluster
 
traceClusters - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
traces - Variable in class org.processmining.pmind.models.DMNModel
 
trainCV(int, int) - Method in class weka.core.Instances
Creates the training set for one fold of a cross-validation on the dataset.
trainCV(int, int, Random) - Method in class weka.core.Instances
Creates the training set for one fold of a cross-validation on the dataset.
TrainedModel - Class in org.processmining.pmind.algorithms.concept
 
TrainedModel(DMNActivity, DMNAttribute, Collection<Integer>) - Constructor for class org.processmining.pmind.algorithms.concept.TrainedModel
 
trueNegativeRate(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculate the true negative rate with respect to a particular class.
truePositiveRate(int) - Method in class weka.classifiers.evaluation.Evaluation
Calculate the true positive rate with respect to a particular class.

U

unclassified() - Method in class weka.classifiers.evaluation.Evaluation
Gets the number of instances not classified (that is, for which no prediction was made by the classifier).
unweightedMacroFmeasure() - Method in class weka.classifiers.evaluation.Evaluation
Unweighted macro-averaged F-measure.
unweightedMicroFmeasure() - Method in class weka.classifiers.evaluation.Evaluation
Unweighted micro-averaged F-measure.
updateMargins(double[], int, double) - Method in class weka.classifiers.evaluation.Evaluation
Update the cumulative record of classification margins.
updateNumericScores(double[], double[], double) - Method in class weka.classifiers.evaluation.Evaluation
Update the numeric accuracy measures.
updatePriors(Instance) - Method in class weka.classifiers.evaluation.Evaluation
Updates the class prior probabilities or the mean respectively (when incrementally training).
updateStatsForClassifier(double[], Instance) - Method in class weka.classifiers.evaluation.Evaluation
Updates all the statistics about a classifiers performance for the current test instance.
updateStatsForConditionalDensityEstimator(ConditionalDensityEstimator, Instance, double) - Method in class weka.classifiers.evaluation.Evaluation
Updates stats for conditional density estimator based on current test instance.
updateStatsForIntervalEstimator(IntervalEstimator, Instance, double) - Method in class weka.classifiers.evaluation.Evaluation
Updates stats for interval estimator based on current test instance.
updateStatsForPredictor(double, Instance) - Method in class weka.classifiers.evaluation.Evaluation
Updates all the statistics about a predictors performance for the current test instance.
useNoPriors() - Method in class weka.classifiers.evaluation.Evaluation
disables the use of priors, e.g., in case of de-serialized schemes that have no access to the original training set, but are evaluated on a set set.

V

valueOf(String) - Static method in enum org.processmining.pmind.parameters.PMInDParameters.MinerType
Returns the enum constant of this type with the specified name.
values() - Static method in enum org.processmining.pmind.parameters.PMInDParameters.MinerType
Returns an array containing the constants of this enum type, in the order they are declared.
variance(int) - Method in class weka.core.Instances
Computes the variance for a numeric attribute.
variance(Attribute) - Method in class weka.core.Instances
Computes the variance for a numeric attribute.
variances() - Method in class weka.core.Instances
Computes the variance for all numeric attributes simultaneously.

W

weakEquals(Object) - Method in class org.processmining.pmind.models.DMNActivityAttributePair
 
weightedAreaUnderPRC() - Method in class weka.classifiers.evaluation.Evaluation
Calculates the weighted (by class size) AUPRC.
weightedAreaUnderROC() - Method in class weka.classifiers.evaluation.Evaluation
Calculates the weighted (by class size) AUC.
weightedFalseNegativeRate() - Method in class weka.classifiers.evaluation.Evaluation
Calculates the weighted (by class size) false negative rate.
weightedFalsePositiveRate() - Method in class weka.classifiers.evaluation.Evaluation
Calculates the weighted (by class size) false positive rate.
weightedFMeasure() - Method in class weka.classifiers.evaluation.Evaluation
Calculates the macro weighted (by class size) average F-Measure.
weightedMatthewsCorrelation() - Method in class weka.classifiers.evaluation.Evaluation
Calculates the weighted (by class size) matthews correlation coefficient.
weightedPrecision() - Method in class weka.classifiers.evaluation.Evaluation
Calculates the weighted (by class size) precision.
weightedRecall() - Method in class weka.classifiers.evaluation.Evaluation
Calculates the weighted (by class size) recall.
weightedTrueNegativeRate() - Method in class weka.classifiers.evaluation.Evaluation
Calculates the weighted (by class size) true negative rate.
weightedTruePositiveRate() - Method in class weka.classifiers.evaluation.Evaluation
Calculates the weighted (by class size) true positive rate.
weka.classifiers.evaluation - package weka.classifiers.evaluation
 
weka.core - package weka.core
 
wekaAttributes - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
wekaStaticWrapper(Sourcable, String) - Static method in class weka.classifiers.evaluation.Evaluation
Wraps a static classifier in enough source to test using the weka class libraries.
wekaUnescape(String) - Static method in class org.processmining.datadiscovery.plugins.DecisionMining
 
writeEventLog(XLog, String) - Static method in class org.processmining.pmind.logs.EventLogOperations
 

X

xLogInfo - Variable in class org.processmining.pmind.algorithms.AbstractDMNMiner
 
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