MATH 7560 - Statistical Learning II

Credits: 3

Sequel to DATA/MATH 7550. Statistical learning and data mining methodologies, both supervised for prediction and classification and unsupervised for clustering and dimension reduction. This course will cover topics selected from supervised learning: model selection and evaluation; bootstrap and cross-validation; tree methods, bagging, random forests, boosting; generalized additive models (GAM) and multivariate adaptive regression splines (MARS); support vector machines (SVM) and neural networks; unsupervised learning: clustering and dimension reduction. Prerequisites: DATA 7550 or MATH 7550, or consent of instructor.

Repeatable:
No