Statistical learning: nonparametric regression and classification (2021)

  • Date:

    18 JANUARY
    -
    27 JANUARY 2021
     from 10:00 to 13:00
  • Event location: Via Teams

  • Type: Cycle 36 - Mandatory Courses

All dates: TBA

Lessons schedule

Mon 18/01 ore 10-13
Wed 20/01 ore 10-13
Fri    22/01 ore 10-12
Mon 25/01 ore 10-13
Wed 27/01 ore 10-13

 

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
    • 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