A Unified Approach for Measuring Precision and Generalization Based on Anti-alignments

Boudewijn F. van Dongen (1) , J Carmona (2) , T F Chatain (3, 4)

1 TU/e - Eindhoven University of Technology [Eindhoven]
2 UPC - Universitat Politècnica de Catalunya = Université polytechnique de Catalogne [Barcelona]
3 MEXICO - Modeling and Exploitation of Interaction and Concurrency
4 LSV - Laboratoire Spécification et Vérification [Cachan]

The holy grail in process mining is an algorithm that, given an event log, produces fitting, precise, properly generalizing and simple process models. While there is consensus on the existence of solid metrics for fitness and simplicity , current metrics for precision and generalization have important flaws, which hamper their applicability in a general setting. In this paper, a novel approach to measure precision and generalization is presented, which relies on the notion of anti-alignments. An anti-alignment describes highly deviating model traces with respect to observed behavior. We propose metrics for precision and generalization that resemble the leave-one-out cross-validation techniques, where individual traces of the log are removed and the computed anti-alignment assess the model's capability to describe precisely or generalize the observed behavior.

Domaines: Théorie et langage formel [cs.FL]

Boudewijn F. van Dongen, J Carmona, T F Chatain. A Unified Approach for Measuring Precision and Generalization Based on Anti-alignments. 14th International Conference on Business Process Management (BPM'16), Sep 2016, Rio de Janeiro, Brazil. pp.39 - 56, ⟨10.1007/978-3-319-45348-4_3⟩. ⟨hal-01406850⟩