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
Cassidy, B., Reeves, N. D., Pappachan, J. M., Gillespie, D., O'Shea, C., Rajbhandari, S., . . . Yap, M. H. (2021). The DFUC 2020 dataset: Analysis towards diabetic foot ulcer detection. European Endocrinology, 1(1), 5-11. doi:10.17925/EE.2021.1.1.5
Jia, Y., Frank, E., Pfahringer, B., Bifet, A., & Lim, N. (2021). Studying and exploiting the relationship between model accuracy and explanation quality. In N. Oliver, F. Pérez-Cruz, S. Kramer, J. Read, & J. A. Lozano (Eds.), Machine Learning and Knowledge Discovery in Databases. Research Track. ECML PKDD 2021. Lecture Notes in Computer Science Vol. 12976 (pp. 699-714). Cham: Springer. doi:10.1007/978-3-030-86520-7_43 Open Access version: https://hdl.handle.net/10289/14561
Gouk, H., Frank, E., Pfahringer, B., & Cree, M. J. (2021). Regularisation of neural networks by enforcing Lipschitz continuity. Machine Learning, 110, 393-416. doi:10.1007/s10994-020-05929-w Open Access version: https://hdl.handle.net/10289/14147
Yap, M. H., Hachiuma, R., Alavi, A., Brüngel, R., Cassidy, B., Goyal, M., . . . Frank, E. (2021). Deep learning in diabetic foot ulcers detection: A comprehensive evaluation. Computers in Biology and Medicine, 135, 104596. doi:10.1016/j.compbiomed.2021.104596 Open Access version: https://hdl.handle.net/10289/14444
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Keywords
Data mining; Machine Learning