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Archived teaching schedules 2018–2019
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MTTA2 Modern Applied Regression Techniques 5 ECTS
Periods
Period I Period II Period III Period IV
Language of instruction
English
Type or level of studies
Intermediate studies
Course unit descriptions in the curriculum
Degree Programme in Mathematics and Statistics
Faculty of Natural Sciences

General description

This course will give a detailed overview of statistical models for modern regression and classification with emphasis on applications. A number of examples and case studies will be examined. This course will cover a range of models from linear regression through various classes of more flexible models including fully nonparametric regression models. We will consider both regression and classification problems. Methods such as splines, additive models, multivariate adaptive regression splines (MARS), neural networks, classification and regression trees (CART), linear and flexible discriminant analysis, generalized additive models, nearest- neighbor rules and learning vector quantization will be discussed.

Enrolment for University Studies

Enrolment time has expired

Teachers

Nurudeen Alimi, Teacher responsible
Nurudeen.Alimi[├Ąt]uta.fi

Teaching

8-Apr-2019 – 17-May-2019
Lectures
Tue 9-Apr-2019 - 14-May-2019 weekly at 10-12, LS B3110, Pinni B
Thu 11-Apr-2019 - 16-May-2019 weekly at 10-12, LS B3110, Pinni B
Exceptions:
25-Apr-2019 at 10 –12 , LS B4115, Pinni B
9-May-2019 at 10 –12 , LS B4115, Pinni B
Exercises
Independent work

Evaluation

Numeric 1-5.

Evaluation criteria

The evaluation will be based on assessments of two project assignments applying the various methods to analyze given datasets plus a review of an interesting article that used any of the methods.

Study materials

Textbooks: 

The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Second Edition). Trevor Hastie, Robert Tibshirani and Jerome Friedman.

Applied Linear Regression Models, Fourth Edition by Kutner, Nachtsheim and Neter.

Further information

Recommended preceding studies:

Basic courses of statistics and Regression analysis.

Please note

Students who have completed course MTTA2 Ei-parametrinen regressio can not get full credits of this course because some of the contents overlap.