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
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
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
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
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
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
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
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.
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.
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.