Statistical Learning A

4 units · Graduate courses (200-299)

(Formerly numbered 212.) Lecture, three hours; discussion, one hour. Requisite: course 100A. Elements of statistical learning. Topics include linear regression, classification (logistic regression, discriminant analysis), resampling methods (cross-validation, bootstrap), model selection (subset, stepwise) and regularization (ridge, lasso). Letter grading.