MATH 7550 - Statistical Learning I

Credits: 3

Statistical learning and data mining methodologies. This course will cover methodologies and data analysis for prediction and classification in supervised learning. Topics selected from logistic regression (binary and multiclass), principal component regression (PCR), partial least squares (PLS), model selection and discriminant analysis, regularized methods: ridge, LASSO, elastic net, least angle regression (LAR), model selection; basis expansions, regularization and splines; kernel smoothing methods. Prerequisites: MATH 6410 and MATH 6420, or consent of instructor. Credit cannot be received for both MATH 7550 and DATA 7550.

Repeatable:
No