Dr. Thomas Weise

Publications on Data Mining

Data Mining means to extract yet-unknown knowledge from raw data. As a researcher working on optimization, I of course also came across this topic. Although this is not my major research area, I could make some contributions. As I am now focusing on benchmarking of optimization methods and extracting high-level information from benchmark results, I will probably be able to venture into this field a bit more.

  1. Thomas Weise and Raymond Chiong. An Alternative Way of Presenting Statistical Test Results when Evaluating the Performance of Stochastic Approaches. Neurocomputing, 147:235-238, January 5, 2015.
    Supersedes technical report Thomas Weise: “Illustration of Statistical Test Results for Experiment Evaluation”, 2011
    details / doi:10.1016/j.neucom.2014.06.071 / pdf icon pdf
  2. Thomas Weise, Raymond Chiong, Ke Tang, Jörg Lässig, Shigeyoshi Tsutsui, Wenxiang Chen, Zbigniew Michalewicz, and Xin Yao. Benchmarking Optimization Algorithms: An Open Source Framework for the Traveling Salesman Problem. IEEE Computational Intelligence Magazine (CIM), 9(3):40-52, August 2014. Featured article and selected paper at the website of the IEEE Computational Intelligence Society (http://cis.ieee.org/).
    details / doi:10.1109/MCI.2014.2326101 / pdf icon pdf
  3. Pu Wang, Ke Tang, Thomas Weise, Edward P.K. Tsang, and Xin Yao. Multiobjective Genetic Programming for Maximizing ROC Performance. Neurocomputing, 125:102-118, February 11, 2014.
    details / doi:10.1016/j.neucom.2012.06.054 / pdf icon pdf
  4. Mani Abedini, Michael Kirley, Raymond Chiong, and Thomas Weise. GPU Accelerated eXtended Classifier System. In Proceedings of the 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM'13), Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI'13), pages 293-300, Singapore: Grand Copthorne Waterfront Hotel, April 16–19, 2013. ISBN 9781467358958, Los Alamitos, CA, USA: IEEE Computer Society Press.
    details / doi:10.1109/CIDM.2013.6597250 / pdf icon pdf
  5. Xiannian Fan, Ke Tang, and Thomas Weise. Margin-Based Over-Sampling Method for Learning From Imbalanced Datasets. In Joshua (Zhexue) Huang, Longbing Cao, and Jaideep Srivastava, editors, Proceedings of the 15th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, Part II (PAKDD'11), volume 6635 of Lecture Notes in Computer Science (LNCS), pages 309-320, Shenzhen, Guangdong, China, May 24–27, 2011. Berlin, Germany: Springer-Verlag GmbH.
    details / doi:10.1007/978-3-642-20847-8_26 / pdf icon pdf
  6. Thomas Weise. Illustration of Statistical Test Results for Experiment Evaluation. Technical Report, Hefei, Anhui, China: University of Science and Technology of China (USTC), School of Computer Science and Technology, Nature Inspired Computation and Applications Laboratory (NICAL), March 2, 2011.
  7. Pu Wang, Thomas Weise, and Raymond Chiong. Novel Evolutionary Algorithms for Supervised Classification Problems: An Experimental Study. Evolutionary Intelligence, 4(1):3-16, March 2011.
    details / doi:10.1007/s12065-010-0047-7 / pdf icon pdf
  8. Pu Wang, Edward P.K. Tsang, Thomas Weise, Ke Tang, and Xin Yao. Using GP to Evolve Decision Rules for Classification in Financial Data Sets. In Fuchun Sun, Yingxu Wang, Jianhua Lu, Bo Zhang, Witold Kinsner, and Lotfi A. Zadeh, editors, Proceedings of the 9th IEEE International Conference on Cognitive Informatics (ICCI'10), pages 720-727, Beijing, China: Tsinghua University, July 7–9, 2010. ISBN: 978-1-4244-8040-1, Los Alamitos, CA, USA: IEEE Computer Society Press.
    details / doi:10.1109/COGINF.2010.5599820 / pdf icon pdf / pdf icon slides
  9. Thomas Weise and Raymond Chiong. Evolutionary Data Mining Approaches for Rule-based and Tree-based Classifiers. In Fuchun Sun, Yingxu Wang, Jianhua Lu, Bo Zhang, Witold Kinsner, and Lotfi A. Zadeh, editors, Proceedings of the 9th IEEE International Conference on Cognitive Informatics (ICCI'10), pages 696-703, Beijing, China: Tsinghua University, July 7–9, 2010. ISBN: 978-1-4244-8040-1, Los Alamitos, CA, USA: IEEE Computer Society Press.
    details / doi:10.1109/COGINF.2010.5599821 / pdf icon pdf / pdf icon slides
  10. Thomas Weise, Stefan Achler, Martin Göb, Christian Voigtmann, and Michael Zapf. Evolving Classifiers – Evolutionary Algorithms in Data Mining. Kasseler Informatikschriften (KIS) 2007, 4, Kassel, Hesse, Germany: University of Kassel, Fachbereich 16: Elektrotechnik/Informatik, September 28, 2007.
    urn:nbn:de:hebis:34-2007092819260