pm4py.algo.evaluation package#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.
Website: https://processintelligence.solutions Contact: info@processintelligence.solutions
Subpackages#
- pm4py.algo.evaluation.earth_mover_distance package
- pm4py.algo.evaluation.generalization package
- pm4py.algo.evaluation.precision package
- pm4py.algo.evaluation.replay_fitness package
- pm4py.algo.evaluation.simplicity package
Submodules#
pm4py.algo.evaluation.algorithm module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.
Website: https://processintelligence.solutions Contact: info@processintelligence.solutions
- class pm4py.algo.evaluation.algorithm.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[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
Dictionary containing fitness, precision, generalization and simplicity; along with the average weight of these metrics