ILP Miner

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.


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

The Event Log as input

Output Ports

The mined Petri net

Popular Predecessors

Popular Successors


This node has no views




You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.