Yale: Rapid prototyping for complex data mining tasks I Mierswa, M Wurst, R Klinkenberg, M Scholz, T Euler Proceedings of the 12th ACM SIGKDD international conference on Knowledge …, 2006 | 1635 | 2006 |
RapidMiner: Data mining use cases and business analytics applications R Klinkenberg Chapman and Hall/CRC, 2013 | 811* | 2013 |
Detecting Concept Drift with Support Vector Machines. R Klinkenberg, T Joachims ICML, 487-494, 2000 | 697 | 2000 |
Learning drifting concepts: Example selection vs. example weighting R Klinkenberg Intelligent Data Analysis 8 (3), 281-300, 2004 | 661 | 2004 |
Adaptive information filtering: Learning drifting concepts R Klinkenberg, I Renz Proc. of AAAI-98/ICML-98 workshop Learning for Text Categorization, 33-40, 1998 | 269* | 1998 |
Boosting classifiers for drifting concepts M Scholz, R Klinkenberg Intelligent Data Analysis 11 (1), 3-28, 2007 | 194 | 2007 |
An ensemble classifier for drifting concepts M Scholz, R Klinkenberg Proceedings of the Second International Workshop on Knowledge Discovery in …, 2005 | 133 | 2005 |
Yale: Yet another learning environment O Ritthoff, R Klinkenberg, S Fischer, I Mierswa, S Felske LLWA 01-Tagungsband der GI-Workshop-Woche, Dortmund, Germany, 84-92, 2001 | 89 | 2001 |
Using labeled and unlabeled data to learn drifting concepts R Klinkenberg Workshop notes of the IJCAI-01 Workshop on Learning from Temporal and …, 2001 | 75 | 2001 |
A hybrid approach to feature selection and generation using an evolutionary algorithm O Ritthof, R Klinkenberg, S Fischer, I Mierswa UK Workshop on Computational Intelligence, 147-154, 2002 | 70 | 2002 |
Concept drift and the importance of examples R Klinkenberg Text mining–theoretical aspects and applications, 2003 | 67 | 2003 |
Yale: Yet Another Learning Environment–Tutorial S Fischer, R Klinkenberg, I Mierswa, O Ritthoff Colloborative Research Center 531, 2002 | 63 | 2002 |
Meta-Learning, Model Selection, and Example Selection in Machine Learning Domains with Concept Drift. R Klinkenberg LWA 2005, 164-171, 2005 | 47 | 2005 |
A flexible platform for knowledge discovery experiments: Yale–yet another learning environment I Mierswa, R Klinkenberg, S Fischer, O Ritthoff Proc. of LLWA 2003, 2, 2003 | 42 | 2003 |
Knowledge discovery from data streams J Gama, J Aguilar-Ruiz, R Klinkenberg Intelligent Data Analysis 12 (3), 251-252, 2008 | 27 | 2008 |
Data mining-supported generation of assembly process plans R Wallis, O Erohin, R Klinkenberg, J Deuse, F Stromberger Procedia Cirp 23, 178-183, 2014 | 22 | 2014 |
Defining Software Architectures for Big Data Enabled Operator Support Systems B Klöpper, M Dix, L Schorer, A Ampofo, M Atzmueller, D Arnu, ... Proc. IEEE International Conference on Industrial Informatics. IEEE, Boston …, 2016 | 19 | 2016 |
Conception of a Reference Architecture for Machine Learning in the Process Industry R Wöstmann, P Schlunder, F Temme, R Klinkenberg, J Kimberger, ... 2020 IEEE International Conference on Big Data (Big Data), 1726-1735, 2020 | 13 | 2020 |
Predicting phases in business cycles under concept drift R Klinkenberg Proc. of LLWA, 3-10, 2003 | 13 | 2003 |
Yale: Yet another learning environment S Fischer, R Klinkenberg, I Mierswa, O Ritthoff HT014601767, 2003 | 13 | 2003 |