DATA 512 Predictive Analytics: Estimation and Clustering
Investigation and application of analytical methods for prediction, using estimation models and clustering models. Topics will include regression modeling, multiple regression modeling, model building, dimension reduction methods, k-means clustering, and evaluating cluster goodness. Further topics may include hierarchical clustering, Kohonen networks clustering, and BIRCH clustering.
Credits
4
Prerequisite
DATA 511 or permission of department chair.