Title: Data Science, Classification, Clustering and Three-Way Data
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 discussed and applied. The problems discussed include data with outliers, longitudinal data, and three-way data. The proposed approaches are generally mixture model-based.
Paul McNicholas is a Professor and University Scholar in the Department of Mathematics and Statistics at McMaster University. His research focuses on computational statistics, data science and machine learning, especially mixture model-based clustering and classification.