Statistical Data Mining II
EAS-507LEC-ST
University at Buffalo
- Semester
- Spring 2025
- Instructor
- Rachael Hageman Blair
- Start Date
- 01-22-2025
- Total Credits
- 3
- Call to Register
- 716-645-5698
Take your class online with SUNY
You will learn the same curriculum as our on-campus students
This course presents the topic of data mining from a statistical perspective, with attention directed towards both applied and theoretical considerations. An emphasis will be placed on supervised learning methods. Topics include: linear and logistic regression, discriminant analysis, shrinkage methods, subset selection, dimension reduction techniques, classification and regression trees, ensemble methods, neural networks, deep feedforward networks, and random forests. Model selection and estimation of generalization error will be emphasized. Considerations and issues that arise with high-dimensional (N<
Course Area: Engineering
Level: Graduate
Dates: 01-22-2025 - 05-06-2025
- Find books for your online class
- Instructor: Rachael Hageman Blair
- Local Course ID: 25SP_BUF_EAS507_LECST
- Books & Supplies
-
How to Register for an Online Course
Let's put your mind at ease about online learning
-
- Search
- Search for an online course by keyword, semester, campus, area, or a combination of each.
-
- Select Course
- Select a course from the results list that fits your needs.
-
- Visit College Website
- Click “register now” to visit the college website to register as a “non-credit” or “non-matriculated” student if you are not enrolled at the campus.
-
- Contact Registrar
- Contact the registrar’s office or enrollment office to register for the course. Make sure you have the course name and course ID when you register.
-
- Transfer Credits
- If you plan to transfer credit for the course, make sure you have reviewed the course with the advisor at your current college to ensure the credits will transfer to your degree program.
-
- Locate Course Materials
- Once you register for the course, visit the campus bookstore to find the books and materials for the course. You will need the course ID to find the books.