PUBH7475: Statistical Learning and Data Mining

3 Credits

Various statistical techniques for extracting useful information (i.e., learning) from data. Linear discriminant analysis, tree-structured classifiers, feed-forward neural networks, support vector machines, other nonparametric methods, classifier ensembles, unsupervised learning. prereq: [[[6450, 6452] or equiv], programming backgroud in [FORTRAN or C/C++ or JAVA or Splus/R]] or instr consent; 2nd yr MS recommended

View on University Catalog

All Instructors

A- Average (3.539)Most Common: A (28%)

This total also includes data from semesters with unknown instructors.

134 students
SWFDCBA
  • 5.23

    /6

    Recommend
  • 5.29

    /6

    Effort
  • 5.57

    /6

    Understanding
  • 5.44

    /6

    Interesting
  • 5.30

    /6

    Activities


      Contribute on our Github

      Gopher Grades is maintained by Social Coding with data from Summer 2017 to Spring 2025 provided by the University in response to a public records request

      Not affiliated with the University of Minnesota

      Privacy Policy