Search Results for author:
Found 3 papers, 2 papers with code
Measuring the Stability of Process Outcome Predictions in Online Settings
This paper proposes an evaluation framework for assessing the stability of models for online predictive process monitoring.
The Analysis of Online Event Streams: Predicting the Next Activity for Anomaly Detection
We compare these predictive anomaly detection methods to four classical unsupervised anomaly detection approaches (such as Isolation forest and LOF) in the online setting.
Explainable Predictive Process Monitoring: A User Evaluation
The results of the user evaluation show that, although explanation plots are overall understandable and useful for decision making tasks for Business Process Management users -- with and without experience in Machine Learning -- differences exist in the comprehension and usage of different plots, as well as in the way users with different Machine Learning expertise understand and use them.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
