STAT 522 Clustering and Affinity Analysis

Investigation and application of methods and models used for clustering and affinity analysis. Topics may include dimension reduction methods, k-means clustering, hierarchical clustering, Kohonen networks clustering, BIRCH clustering, anomaly detection, market basket analysis, and association rules using the a priori and generalized rule induction algorithms.

Credits

4

Prerequisite

STAT 521 or permission of department chair.

General Education

Offered

  • Spring