Statistical learning: nonparametric regression and classification

Prof. Giuliano Galimberti

  • Date:

    02 APRIL
    -
    18 APRIL 2019
     from 14:00 to 17:00

  • Event location: Seminar Room, 1st floor, Department of Statistical Science, Via Belle Arti 41, Bologna

  • Type: Cycle 34 - Mandatory Courses

Prof. Giuliano Galimberti

02/04: 14.00 - 17.00

04/04: 14.00 - 17.00

11/04: 10.00 - 13.00

18/04: 14.00 - 17.00

* Topics:

  • Overview
  • Generalized additive models
    • Definition
    • Model fitting
    • Choice of the smoothing parameters
  • Tree-based methods
    • Background
    • Regression trees
    • Classification trees
  • Ensemble methods
    • Weak learners
    • Bagging
    • Boosting
    • Random forests
    • Variable importance measures


* References:

James G., Witten D., Hastie T. and Tibshirani R. (2013). An Introduction to Statistical Learning. Springer.
Hastie T., Tibshirani R. and Friedman J. (2009). The Elements of Statistical Learning (second edition). Springer