Semester 2 2015/16

Tuesday 14-17, Dan-David 204

Home page on http://www.tau.ac.il/ ∼ saharon/IntroStatLearn.html

Tuesday 14-17, Dan-David 204

Home page on http://www.tau.ac.il/ ∼ saharon/IntroStatLearn.html

Lecturer: | Saharon Rosset |

Schreiber 022 | |

saharon@post.tau.ac.il | |

Office hrs: | Thursday 16-17 or by appointment (coordination needed in any case). |

The topics we will cover include:

- Introduction: some examples of problems in regression and classification; Focus on Google Flu Trends (GFT)
- Basic methods for regression: Linear regression and local (neighbor-based) methods
- Basic methods for classification: Logistic regression and discriminant analysis
- Resampling methods: cross validation and bootstrap
- Model selection and regularization
- Modern methods and their applications: trees, support vector machines

The grade will be a combination of homework problem sets (about six overall, worth about 30% of final grade) and a final in-class exam (about 70% of final grade).

Undergraduate courses in: Probability; Regression; Theoretical Statistics (possibly in parallel)

Statistical programming experience in

R Project website also contains extensive documentation.

A basic "getting you started in R" tutorial. Uses the Boston Housing Data (thanks to Giles Hooker).

File translated from T

On 13 Jun 2016, 17:02.