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Does Your Accurate Process Predictive Monitoring Model Give Reliable Predictions?

  • Marco ComuzziEmail author
  • Alfonso E. Marquez-Chamorro
  • Manuel Resinas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11434)

Abstract

The evaluation of business process predictive monitoring models usually focuses on accuracy of predictions. While accuracy aggregates performance across a set of process cases, in many practical scenarios decision makers are interested in the reliability of an individual prediction, that is, an indication of how likely is a given prediction to be eventually correct. This paper proposes a first definition of business process prediction reliability and shows, through the experimental evaluation, that metrics that include features defining the variability of a process case often give a better prediction reliability indication than metrics that include the probability estimation computed by the machine learning model used to make predictions alone.

Keywords

Business process Predictive monitoring Reliability 

References

  1. 1.
    Bosnić, Z., Kononenko, I.: An overview of advances in reliability estimation of individual predictions in machine learning. Intell. Data Anal. 13(2), 385–401 (2009)CrossRefGoogle Scholar
  2. 2.
    Bosnić, Z., Kononenko, I.: Estimation of individual prediction reliability using the local sensitivity analysis. Appl. Intell. 29(3), 187–203 (2008)CrossRefGoogle Scholar
  3. 3.
    Márquez-Chamorro, A., Resinas, M., Ruiz-Cortés, A., Toro, M.: Run-time prediction of business process indicators using evolutionary decision rules. Expert Syst. Appl. 87(Supplement C), 1–14 (2017)CrossRefGoogle Scholar
  4. 4.
    Marquez-Chamorro, A.E., Resinas, M., Ruiz-Cortes, A.: Predictive monitoring of business processes: a survey. IEEE Trans. Serv. Comput. 11, 962–977 (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Marco Comuzzi
    • 1
    Email author
  • Alfonso E. Marquez-Chamorro
    • 2
  • Manuel Resinas
    • 2
  1. 1.Ulsan National Institute of Science and TechnologyUlsanRepublic of Korea
  2. 2.Universidad de SevillaSevillaSpain

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