pm4py.algo.evaluation.algorithm module#
PM4Py – A Process Mining Library for Python
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- class pm4py.algo.evaluation.algorithm.Parameters(*values)[source]#
Bases:
Enum- ACTIVITY_KEY = 'pm4py:param:activity_key'#
- PARAM_FITNESS_WEIGHT = 'fitness_weight'#
- PARAM_PRECISION_WEIGHT = 'precision_weight'#
- PARAM_SIMPLICITY_WEIGHT = 'simplicity_weight'#
- PARAM_GENERALIZATION_WEIGHT = 'generalization_weight'#
- pm4py.algo.evaluation.algorithm.apply(log: EventLog | DataFrame, net: PetriNet, initial_marking: Marking, final_marking: Marking, parameters: Dict[str | Parameters, Any] | None = None) Dict[str, float][source]#
Calculates all metrics based on token-based replay and returns a unified dictionary
- Parameters:
log – Log
net – Petri net
initial_marking – Initial marking
final_marking – Final marking
parameters – Parameters
- Returns:
Dictionary containing fitness, precision, generalization and simplicity; along with the average weight of these metrics
- Return type:
dictionary