3unit(s) Cluster analysis techniques. Dissimilarities and distances. Hierarchical clustering, distance-based clustering, fuzzy clustering, spectral clustering, subspace clustering, categorical data clustering. Clustering method for high dimensional datasets.
Prerequisite(s):MATH 32 or MATH 32H, MATH 39 (each with a grade of “B” or better), MATH 163 and MATH 167R or CS 122. Or instructor consent. Grading: Letter Graded