MATH 6392 Statistical Learning
This course introduces the statistical tools of supervised and unsupervised learning including topics of regression and clssification, such as linear regression, multiple regression, logistic regression, K-nearest neighbors, polynomial regression, splines regression, tree regression, random forests, ridge regression and the Lasso, linear and quadratic discriminant analysis, support vector classifiers and machines. In this course, students are required to use a statitiscal software to carry out the procedures.
Prerequisite
Consent of instructor
Offered
As scheduled