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EECS 839 Mining Special Data

EECS 839.  Mining Special Data.  3 Credits.     

Problems associated with mining incomplete and numerical data. The MLEM2 algorithm for rule induction directly from incomplete and numerical data. Association analysis and the Apriori algorithm. KNN and other statistical methods. Mining financial data sets. Problems associated with imbalanced data sets and temporal data. Mining medical and biological data sets. Induction of rule generations. Validation of data mining: sensitivity, specificity, and ROC analysis. Prerequisite: Graduate standing in CS or CoE or consent of instructor.

Doctor of Philosophy in Business

http://catalog.ku.edu/business/phd/

...Intelligence 3 EECS 738 Machine Learning 3 EECS 837 Data Mining 3 EECS 839 Mining...