CLRE 267Machine Learning and Predictive Analytics in Biomedical Research
The course introduces tools and practices for predictive modeling of binary, categorical, and continuous outcomes, using the R statistical software. The methods include linear and logistic regression using LASSO, ridge regression and elastic nets, CART, boosting, bagging, and random forests. Corequisite: CLRE 254.
Prerequisites
From the catalog: “CLRE 253, admission to the MAS in Clinical Research Program, or consent of department.”