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EECS 837 Data Mining

EECS 837.  Data Mining.  3 Credits.     

Extracting data from data bases to data warehouses. Preprocessing of data: handling incomplete, uncertain, and vague data sets. Discretization methods. Methodology of learning from examples: rules of generalization, control strategies. Typical learning systems: ID3, AQ, C4.5, and LERS. Validation of knowledge. Visualization of knowledge bases. Data mining under uncertainty, using approaches based on probability theory, fuzzy set theory, and rough set theory. Prerequisite: Graduate standing in CS or CoE or consent of instructor.

Master of Science in Physics

...3 EECS 738 Machine Learning 3 EECS 739 Parallel Scientific Computing 3 EECS 837 Data...

Doctor of Philosophy in Business

...3 EECS 649 Introduction to Artificial Intelligence 3 EECS 738 Machine Learning 3 EECS 837...