Predictive Business Process Monitoring Framework with Hyperparameter Optimization
نویسندگان
چکیده
Predictive business process monitoring exploits event logs to predict how ongoing (uncompleted) cases will unfold up to their completion. A predictive process monitoring framework collects a range of techniques that allow users to get accurate predictions about the achievement of a goal or about the time required for such an achievement for a given ongoing case. These techniques can be combined and their parameters configured in different framework instances. Unfortunately, a unique framework instance that is general enough to outperform others for every dataset, goal or type of prediction is elusive. Thus, the selection and configuration of a framework instance needs to be done for a given dataset. This paper presents a predictive process monitoring framework armed with a hyperparameter optimization method to select a suitable framework instance for a given dataset.
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