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.

General Education

Offered

• Spring

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