Data science is discussed along with some historical perspective. Selected problems in classification are considered, either via specific datasets or general problem types. In each case, the problem is introduced before one or more potential solutions are considered. The problems discussed include data with outliers, longitudinal data, and three-way data. The proposed approaches are generally mixture model-based.
Paul McNicholas is the Canada Research Chair in Computational Statistics and an E.W.R. Steacie Memorial Fellow at McMaster University, where he is a Professor and University Scholar in the Department of Mathematics and Statistics as well as Director of the MacDATA Institute. He completed his Ph.D. in Statistics at Trinity College Dublin in 2007. He has published extensively in computational statistics, with the vast majority of his journal articles, and one of his monographs, focusing on mixture model-based clustering and related topics. He has been an associate or guest editor for several international journals, and is currently Editor-in-Chief of Journal of Classification. He is the winner of the 2020 Steacie Prize for the Natural Sciences and a member of the College of the Royal Society of Canada.