MATH 342 - Multiple Regression and Machine Learning Methods
3 Credits
Description
Multiple regression and related machine learning methods including ridge regression, lasso, elasticnet, and neural networks. Classifaction methods: logistic regreassion and linear discriminant analysis. Unsupervised methods: principal components and clustering. Modern modelling methods including bootstrapping and cross-validation.
Prerequisites
MATH 341 with a C or better.
Repeatable
No
Click here for the Fall 2025 Class Schedule
Click here for the Spring 2026 Class Schedule
Click here for the Summer 2026 Class Schedule
Add to Portfolio (opens a new window)
|