TILS646 Clustering, Classification and Regression Methods (4–5 cr)

Study level:
Advanced studies
Grading scale:
0-5
Language:
Finnish
Responsible organisation:
Department of Mathematics and Statistics
Curriculum periods:
2020-2021, 2021-2022, 2022-2023, 2023-2024

Description

The course gives an overview over clustering and classification methods as well how to validate the results. Also nonlinear regression methods for numeric responses are shortly covered

The course covers key data grouping methods and the validation of related results, key classification methods and validation of their results, and a few non-linear regression methods of continuous response, as time permits. The course focuses on data analysis.

Learning outcomes

Successful completion of the course students can distinguish between clustering and classification methods and are familar with several of these methods. Also the performance of these methods can be evaluated.

Furthermore are students familiar with basic concepts of non-linear regression. Students will be able to able the methods to real data and interpret and report the results.

Description of prerequisites

Statistical inference 1 and 2, generalized linear models 1 and 2, Multivariate Statistical Methods and basics of R software

Completion methods

Method 1

Evaluation criteria:
The assessment is based on the performance in the weekly tasks as well as in a final assignment.
Select all marked parts

Method 2

Evaluation criteria:
In order to pass the final exam at least half of the maximum points of the exam are usually required.
Select all marked parts
Parts of the completion methods
x

Teaching (4–5 cr)

Type:
Participation in teaching
Grading scale:
0-5
Language:
English, Finnish

Teaching

x

Exam (4–5 cr)

Type:
Exam
Grading scale:
0-5
Language:
Finnish
No published teaching