Professor Eibe Frank
Professor (Computer Science)
Qualifications: Dipl-Inf Karlsruhe PhD Waikato
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
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
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
Coup, S., Vetrova, V., Frank, E., & Tappenden, R. (2019). Domain specific transfer learning using image mixing and stochastic image selection. In The Sixth Workshop on Fine-Grained Visual Categorization (FGVC6), Computer Vision and Pattern Recognition Conference (EVPR 2019) (pp. 4 pages). Long Beach, CA. Retrieved from https://drive.google.com/file/d/14XiBpmeT4h7RUcJj6l7a5hf6xw7L493D/view
Find more research publications by Eibe Frank