MATH 252 - Cluster Analysis

3 unit(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 or MATH 32X, MATH 39 (each with a grade of “B” or better), MATH 163 and MATH 167R or CS 122. Or instructor consent.
Grading: Letter Graded

Class Schedule | Syllabus Information | University Bookstore