STT 6640 - Machine Learning


Credit Hour(s): 3
Classification. Resampling methods including bootstrapping. Regularization. Splines. Classification and regression trees. Bagging and boosting. Random forest. Unsupervised learning including principal component analysis. Software used for this course includes R.
Prerequisite(s): Graduate level STT 5600 Minimum Grade of D and Graduate level STT 5610 Minimum Grade of D
Enrollment Restrictions: Must be enrolled in one of the following Levels: Graduate, Medical, Professional.

Level: Graduate
Schedule Type(s): Lecture

This course information is from the 2023-2024 Academic Catalog. View this catalog.
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