Professor Geoff Holmes
Dean of Computing & Mathematical Sciences
Qualifications: BSc(Hons) PhD S'ton
Phone: +64 7 838 4405
I received my degrees in Mathematics from the University of Southampton, England. My PhD involved the development of software packages to assist Mathematicians in solving Einstein's field equations in General Relativity. This was how I got started in Computer Science. After graduating I became a Research Assistant at the Electrical Engineering Department of Cambridge University, England where I was a member of large team working on a speech understanding system. I took up a position as Lecturer in Computer Science in 1987. In 1993 I was appointed Senior Lecturer.
My research interests are fairly broad. I have always held an interest in Computer Speech and have supervised several projects at Waikato on that topic, in particular, speech recognition and speech compression. I currently have two PhD students working on speech compression. I am part of the Department's Machine Learning group where I concentrate my efforts on the application of Machine Learning to agricultural domains. Through my interests in Machine Learning I have recently become very interested in the concept of knowledge discovery in databases.
Leathart, T., Frank, E., Pfahringer, B., & Holmes, G. (2019). On calibration of nested dichotomies. 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. 69-80). Cham: Springer. doi:10.1007/978-3-030-16148-4_6
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
Gomes, H. M., Bifet, A., Read, J., Barddal, J. P., Enembreck, F., Pfahringer, B., . . . Abdessalem, T. (2019). Correction to: Adaptive random forests for evolving data stream classification (Machine Learning, (2017), 106, 9-10, (1469-1495), 10.1007/s10994-017-5642-8). Machine Learning. doi:10.1007/s10994-019-05793-3
van Rijn, J. N., Holmes, G., Pfahringer, B., & Vanschoren, J. (2018). The online performance estimation framework: heterogeneous ensemble learning for data streams. Machine Learning, 107(1), 149-176. doi:10.1007/s10994-017-5686-9
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