2021
DOI: 10.1109/access.2021.3115759
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Stability Metrics for Enhancing the Evaluation of Outcome-Based Business Process Predictive Monitoring

Abstract: Outcome-based predictive process monitoring deals with predicting the outcomes of running cases in a business process using feature vectors extracted from completed traces in an event log. Traditionally, in outcome-based predictive monitoring, a different model is developed using a bucket containing different types of feature vectors. This allows us to extend the traditional evaluation of the quality of process outcome predictions models beyond simply measuring the overall performance, developing a quality ass… Show more

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Cited by 2 publications
(1 citation statement)
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“…For root cause analysis of predicted compliance violations (CMF9.1), [38] provides input by visualization the impact of activities on the predicted outcome (c/ ∼). There are no approaches that explain and visualize prediction results (CMF9.3), but rather provide metrics for the quality of the prediction results, for example, stability [51] and reliability [54]. Aside these quality metrics, CMF9.1-9.4 are not addressed by outcome prediction approaches.…”
Section: Outcome Anyindicatormentioning
confidence: 99%
“…For root cause analysis of predicted compliance violations (CMF9.1), [38] provides input by visualization the impact of activities on the predicted outcome (c/ ∼). There are no approaches that explain and visualize prediction results (CMF9.3), but rather provide metrics for the quality of the prediction results, for example, stability [51] and reliability [54]. Aside these quality metrics, CMF9.1-9.4 are not addressed by outcome prediction approaches.…”
Section: Outcome Anyindicatormentioning
confidence: 99%