Machine Learning and Predictive Analytics in Biomedical Research

2 credits

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: CLRE 253, admission to the MAS in Clinical Research Program, or consent of department.