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