Mar 28, 2024  
2019-2020 Undergraduate Catalogue 
    
2019-2020 Undergraduate Catalogue Archived Catalogue

STT 450 - Statistical Data Mining


An introduction to the fundamental principles and applications of the most commonly used data mining techniques such as regression, classification, and clustering methods. The data mining techniques may include linear regression, classification, re-sampling methods, linear model selection and regulation, tree-based methods, Support Vector Machines (SVM), and clustering methods. Students will learn how to explore and analyze large high-dimensional real-world apllications to build effective systems for prediction by using standard programming tools.

Credit Hours: 3

Prerequisite Courses: STT 411  or STT 412   or permission of instructor.
Course Repeatablility: Course may not be repeated. Maximum Repeatable Hours: 3



Click here for the Spring 2024 Class Schedule.