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Professor Bernhard Pfahringer

Professor (Computer Science)

Qualifications: MEng PhD Vienna Tech

Contact Details

Email: bernhard@waikato.ac.nz
Room: G.1.24
Phone: +64 7 838 4041
Extension: 4041
Fax: +64 7 858 5095
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).

Research Interests

Data mining, machine learning, heuristic optimisation, programming languages.

Teaching Commitments

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

  • Bifet, A., Read, J., Holmes, G., & Pfahringer, B. (2018). Streaming data mining with Massive Online Analytics (MOA). In M. Last, H. Bunke, & A. Kandel (Eds.), Data Mining in Time Series and Streaming Databases (pp. 1-25).

  • Yogarajan, V., Mayo, M., & Pfahringer, B. (2018). Privacy protection for health information research in New Zealand district health boards. New Zealand Medical Journal, 131(1485), 19-26. Open Access version: https://hdl.handle.net/10289/12161

  • Yuan, L., Pfahringer, B., & Barddal, J. P. (2018). Iterative subset selection for feature drifting data streams. In Proc 33rd Annual ACM Symposium on Applied Computing (SAC 2018) (pp. 510-517). New York, NY: ACM. doi:10.1145/3167132.3167188

Find more research publications by Bernhard Pfahringer