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Ohio State University logo STAT 760 Elements of Statistical Learning Home

Course information

  1. Description:

    Statistical learning or machine learning methodology explores various ways of estimating functional dependencies between a response variable and possibly a large set of explanatory variables (features), when one is trying to find and understand an unknown, regular component within the realm of noisy complex data. Modern regression and pattern recognition analyses fall in this framework. This course will provide an overview of supervised learning and discussions of statistical learning algorithms such as Discriminant Analysis, Classification Tree, Support Vector Machines, and Boosting and illustrate practical uses of the algorithms.

  2. Lecture: MW 3:30-4:48PM in Hayes Hall (HA) 220.
  3. Text: The Elements of Statistical Learning - Data Mining, Inference and Prediction, by Hastie, T., Tibshirani, R., and Friedman, J. (2001).
  4. Instructor:
    Yoonkyung Lee
    Office: 440B Cockins Hall
    Phone: 292-9495
    Office Hours: T 1:30-2:18PM and R 2:30-3:18PM or by appointment
    Email: yklee at stat domain [when e-mailing, replace 'at stat domain' by @stat.osu.edu]
  5. Grader:
    Youlan Rao
    Office: 304G Cockins Hall
    Office Hours: by appointment
    Email: rao at stat domain

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