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ILP Miner

Dummy version 1.0.0.v202003051301 by PADS RWTH Aachen

This nodes wraps the Hybridilpminer from ProM to mine a Petri net from an event log. Multiple algorithms based on transitions theory and ILP are provided.

Options

Event classifer
The classifier is chosen to classify the event log.
Filter Type
The filter type include the following choices:
  • NONE: No filter
  • SEQUENCE_ENCODING: Sequence Encoding Filter specifies at what level a branch should be cut off. In default it is 0.25.
  • SLACK_VAR: Slack Variable Filter specifies what protion of constraints might be shut off. In default, it is 0.25.
Noise Threshold
Noise threshold is to filter the event log. 0.2 is as the default value.
Objective Function
Set the objective function for ILP. There are the following choices.
  • WEIGHTED_ABSOLUTE_PARIKH: Weighted Parikh values, using absolute frequencies
  • WEIGHTED_RELATIVE_PARIKH: Weighted Parikh values, using relative frequencies
  • UNWEIGHTED_PARIKH: Unweighted Parikh values
  • MINIMIZE_ARCS: Minimize Arcs
Variable Distribution
Set LP Variable. There are the following choices.
  • DUAL: Two variables per event.
  • HYBRID: One variable per event, two for an event which is potentially in a self loop.
  • SINGLE: One variable per event.
Discovery Strategy
Set Discovery Strategy. There are the following choices:
  • CAUSAL_FLEX_HEUR: Mine a place per causal relation (flexible heuristics miner)
  • TRANSITION_PAIR: Mine a connecting place between each pair of transitions

Input Ports

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The Event Log as input

Output Ports

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The mined Petri net

Best Friends (Incoming)

Best Friends (Outgoing)

Workflows

Installation

To use this node in KNIME, install Process Mining Extension from the following update site:

KNIME 4.3

A zipped version of the software site can be downloaded here.

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