java.lang.Iterable<DeDuplicatedLog> |
CachedCortadellaMethod.applyDeduplication(org.deckfour.xes.model.XLog inputLog,
NLPLogUtilsParameters nlpParameters,
java.lang.String logName) |
java.lang.Iterable<DeDuplicatedLog> |
CortadellaMethod.applyDeduplication(org.deckfour.xes.model.XLog logFile,
NLPLogUtilsParameters nlpParameters,
java.lang.String logName) |
java.lang.Iterable<DeDuplicatedLog> |
FodinaMethod.applyDeduplication(org.deckfour.xes.model.XLog inputLog,
NLPLogUtilsParameters nlpParameters,
java.lang.String logName) |
java.util.Collection<DeDuplicatedLog> |
LabelerPredictionMethod.applyDeduplication(org.deckfour.xes.model.XLog inputLog,
NLPLogUtilsParameters nlpParameters,
java.lang.String logName) |
java.lang.Iterable<DeDuplicatedLog> |
Method.applyDeduplication(org.deckfour.xes.model.XLog inputLog,
NLPLogUtilsParameters nlpParameters,
java.lang.String logName)
Each method must return a new log based on an input log.
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java.lang.Iterable<DeDuplicatedLog> |
NodeduplicationMethod.applyDeduplication(org.deckfour.xes.model.XLog inputLog,
NLPLogUtilsParameters nlpParameters,
java.lang.String logName) |
java.lang.Iterable<DeDuplicatedLog> |
OurMethod.applyDeduplication(org.deckfour.xes.model.XLog inputLog,
NLPLogUtilsParameters nlpParameters,
java.lang.String logName) |
java.util.Collection<DeDuplicatedLog> |
OurPredictionMethod.applyDeduplication(org.deckfour.xes.model.XLog log,
NLPLogUtilsParameters nlpParameters,
java.lang.String logName) |
java.util.Collection<DeDuplicatedLog> |
XixiMethod.applyDeduplication(org.deckfour.xes.model.XLog log,
NLPLogUtilsParameters nlpParameters,
java.lang.String logName) |
ComplexityResult |
AbstractMethod.getComplexity(org.deckfour.xes.model.XLog inputLog,
org.processmining.plugins.InductiveMiner.efficienttree.EfficientTree effTree,
org.processmining.plugins.InductiveMiner.efficienttree.EfficientTree effFlowerTree,
NLPLogUtilsParameters nlpParameters,
boolean useAlignment) |
DeduplicationResult |
AbstractMethod.getDeduplicationResult(org.deckfour.xes.model.XLog inputLog,
DeDuplicatedLog deDuplicatedLog,
org.processmining.plugins.InductiveMiner.efficienttree.EfficientTree flowerTree,
NLPLogUtilsParameters nlpParameters,
double initialComplexity,
boolean useAlignment) |
org.processmining.plugins.InductiveMiner.efficienttree.EfficientTree |
AbstractMethod.getEfficientFlowerTree(org.deckfour.xes.model.XLog inputLog,
NLPLogUtilsParameters nlpParameters) |
static org.processmining.plugins.InductiveMiner.efficienttree.EfficientTree |
TreeDiscovery.getEfficientTree(org.deckfour.xes.model.XLog inputLog,
DeDuplicatedLog deDuplicatedLog,
NLPLogUtilsParameters nlpParameters) |
static DeDuplicatedLog |
FodinaMethod.getLogWithDuplicateLabels(org.deckfour.xes.model.XLog log,
NLPLogUtilsParameters nlpParameters,
ContextParameters contextParameters) |
static DeDuplicatedLog |
OurMethod.getLogWithDuplicateLabels(org.deckfour.xes.model.XLog log,
NLPLogUtilsParameters nlpParameters,
ContextParameters contextParameters) |
DeDuplicatedLog |
AbstractMethod.selectBestCandidate(java.lang.Iterable<DeDuplicatedLog> deDuplicatedLogs,
org.deckfour.xes.model.XLog inputLog,
NLPLogUtilsParameters nlpParameters) |
DeDuplicatedLog |
Method.selectBestCandidate(java.lang.Iterable<DeDuplicatedLog> logs,
org.deckfour.xes.model.XLog inputLog,
NLPLogUtilsParameters nlpParameters)
Each method must select the best candidate based on a number of logs.
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