Explainable Predictive Process Monitoring

• URL: http://arxiv.org/abs/2008.01807v2
• Date: Wed, 16 Sep 2020 20:03:08 GMT
• Title: Explainable Predictive Process Monitoring
• Authors: Riccardo Galanti, Bernat Coma-Puig, Massimiliano de Leoni, Josep Carmona, Nicol\`o Navarin
• Abstract summary: This paper tackles the problem of equipping predictive business process monitoring with explanation capabilities. We use the game theory of Shapley Values to obtain robust explanations of the predictions. The approach has been implemented and tested on real-life benchmarks, showing for the first time how explanations can be given in the field of predictive business process monitoring.
• Score: 0.5564793925574796
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Predictive Business Process Monitoring is becoming an essential aid for organizations, providing online operational support of their processes. This paper tackles the fundamental problem of equipping predictive business process monitoring with explanation capabilities, so that not only the what but also the why is reported when predicting generic KPIs like remaining time, or activity execution. We use the game theory of Shapley Values to obtain robust explanations of the predictions. The approach has been implemented and tested on real-life benchmarks, showing for the first time how explanations can be given in the field of predictive business process monitoring.

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