Contact Details

Email: eibe@waikato.ac.nz
Room: G.2.18
Phone: +64 7 838 4396
Extension: 4396
Website: http://www.cs.waikato.ac.nz/~eibe/

Research Interests

Professor Frank is a computer scientist whose primary area of interest is machine learning and its applications. He is a core developer of the WEKA machine learning software and has more than 100 publications on machine learning methods and their application to data mining, text mining, and areas of research outside computer science.

Recent Publications

• 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). 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

• Gouk, H., Pfahringer, B., & Frank, E. (2019). Stochastic gradient trees. In W. S. Lee, & T. Suzuki (Eds.), Proc 11th Asian Conference on Machine Learning (ACML 2019) Vol. PMLR 101 (pp. 1094-1109). Nagoya, Japan: PMLR. Retrieved from http://proceedings.mlr.press/v101/gouk19a.html

• Lang, S., Bravo-Marquez, F., Beckham, C., Hall, M., & Frank, E. (2019). WekaDeeplearning4j: A deep learning package for weka based on Deeplearning4j. Knowledge-Based Systems. doi:10.1016/j.knosys.2019.04.013

Find more research publications by Eibe Frank