Professor Bernhard Pfahringer
Professor (Computer Science)
Qualifications: MEng PhD Vienna Tech
Personal Website: http://www.cs.waikato.ac.nz/~bernhard/
About Bernhard
Find out more about Bernhard and his work by viewing his professorial lecture: Dawn of the Age of Data: a Lecture to look at the data revolution (October 2015).
Papers Taught
Research Interests
Data mining, machine learning, heuristic optimisation, programming languages.
Recent Publications
Barddal, J. P., Enembreck, F., Gomes, H. M., Bifet, A., & Pfahringer, B. (2019). Merit-guided dynamic feature selection filter for data streams. Expert Systems with Applications, 116, 227-242. doi:10.1016/j.eswa.2018.09.031
Bravo-Marquez, F., Frank, E., Pfahringer, B., & Mohammad, S. M. (2019). AffectiveTweets: a Weka package for analyzing affect in tweets. Journal of Machine Learning Research, 20, 1-6. Retrieved from http://jmlr.org/papers/v20/18-450.html Open Access version: https://hdl.handle.net/10289/12617
Leathart, T., Frank, E., Pfahringer, B., & Holmes, G. (2019). On calibration of nested dichotomies. In Q. Yang, Z. -H. Zhou, Z. Gong, M. -L. Zhang, & S. -J. Huang (Eds.), Advances in Knowledge Discovery and Data Mining: Proc 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2019), LNCS 11439 Vol. Part I (pp. 69-80). Cham: Springer. doi:10.1007/978-3-030-16148-4_6
Leathart, T., Frank, E., Pfahringer, B., & Holmes, G. (2019). Ensembles of nested dichotomies with multiple subset evaluation. In Q. Yang, Z. -H. Zhou, Z. Gong, M. -L. Zhang, & S. -J. Huang (Eds.), Advances in Knowledge Discovery and Data Mining: Proc 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2019), LNCS 11439 Vol. Part I (pp. 81-93). Cham: Springer. doi:10.1007/978-3-030-16148-4_7
Keywords
Computing; Data mining; Machine Learning
Contact Details
Email: bernhard@waikato.ac.nzRoom: G.1.24
Phone: +64 7 838 4041