Heuristics Miner (Event Log)

This node implements the Heuristics Miner to discover a Petri net from an event log. The Heuristics Miner discovers a heuristics net, which is a directed graph with activities as nodes and edges connecting nodes to model dependencies between activities. The discovered heuristics net is converted into a Petri net.

Options

Event classifer

The attribute to be used as an event classifier.

All tasks connected

If enabled, every task must have at least one input and one output arc (except the initial and the final activity).

Long distance dependency

If enabled, long distance dependencies are shown in the model.

Threshold: Relative-to-best

The percentage for the admissible distance between directly follows relations for an activity and the activity's best one. At 0, only the best directly follows relation will be shown for every activity. At 100, all will be shown.

Threshold: Dependency

A threshold for the strength of the directly follows relation.

Threshold: Length-One-loops

A threshold for the L1L metric.

Threshold: Length-Two-loops

A threshold for the L1L metric.

Threshold: Long Distance

A threshold for the strength of the eventually follows relation.

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