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