Handling Concept Drift in Process Mining

Author:

Bose R. P. Jagadeesh Chandra,van der Aalst Wil M. P.,Žliobaitė Indrė,Pechenizkiy Mykola

Publisher

Springer International Publishing

Reference16 articles.

1. Žliobaitė, I.: Learning under Concept Drift: an Overview. Technical report, Faculty of Mathematics and Informatics, Vilnius University, Vilnius, Lithuania (2009)

2. Pechenizkiy, M., Bakker, J., Žliobaitė, I., Ivannikov, A., Kärkkäinen, T.: Online Mass Flow Prediction in CFB Boilers with Explicit Detection of Sudden Concept Drift. SIGKDD Explorations 11(2), 109–116 (2009)

3. Tsymbal, A., Pechenizkiy, M., Cunningham, P., Puuronen, S.: Handling Local Concept Drift with Dynamic Integration of Classifiers: Domain of Antibiotic Resistance in Nosocomial Infections. In: CBMS, pp. 679–684 (2006)

4. Lecture Notes in Computer Science;B. Weber,2007

5. Mulyar, N.: Patterns for Process-Aware Information Systems: An Approach Based on Colored Petri Nets. PhD thesis, University of Technology, Eindhoven (2009)

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