Statistical Data Mining

3 credits · Graduate

This course covers statistical methodology, major software and applications in data mining. A variety of supervised learning and unsupervised learning methods will be discussed. Topics include: Linea methods for regression and classification, prototype methods, decision trees, additive models, bagging and boosting, neural networks and support vector machines. PREREQUISITES: Permission of instructor FORMATS: Lecture