Professor Bernhard Pfahringer
Professor (Computer Science)
Qualifications: MEng PhD Vienna Tech
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).
Data mining, machine learning, heuristic optimisation, programming languages.
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