Professor Eibe Frank
Professor (Computer Science)
Qualifications: Dipl-Inf Karlsruhe PhD Waikato
Personal 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
Mayo, M., & Frank, E. (2020). Improving naive Bayes for regression with optimised artificial surrogate data. Applied Artificial Intelligence, 34(6), 484--514. doi:10.1080/08839514.2020.1726615 Open Access version: https://hdl.handle.net/10289/12514
Compton, R., Frank, E., Patros, P., & Koay, A. (2020). Embedding Java classes with code2vec: improvements from variable obfuscation [Accepted]. In IEEE/ACM 17th International Conference on Mining Software Repositories (MSR 2020). Seoul, Republic of Korea. doi:10.1145/3379597.3387445 Open Access version: https://hdl.handle.net/10289/13618
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 Open Access version: https://hdl.handle.net/10289/13189
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
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Keywords
Data mining; Machine Learning
Contact Details
| Name | Extn. | Username | Room | Department | ||||
|---|---|---|---|---|---|---|---|---|
| Frank, Prof Eibe | 4396 | eibe | G.2.18 | Computer Science |
You can contact staff by:
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