Statistical Learning

Itai Dattner
Department of Statistics
University of Haifa

Course outline

Some useful information

Introduction

Linear regression

Classification

Exercise 1

Resampling methods

Model selection and regularization

Exercise 2

Moving beyond linearity

Tree-based methods

Exercise 3

Support Vector Machines

Unsupervised Learning

Exercise 4

Additional material PDF file:

   Nonparametric smoothing (density estimation and local regression) - p.228-252 of the PDF.

   PCA - p.284-296 of the PDF.

   Multidimensional scaling - p.354-380 of the PDF.

   Association rules - p.33-57 of the PDF.

Exam

Solution