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.