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.