732A32 Data mining project
The aim of this course is that, after its completion, the student is able to
- apply previously obtained knowledge in the field of data mining in a real setting,
- plan, perform and report on an individual task, and
- demonstrate insight in research and development work.
- Your own project, send a brief description to Jose M. Pena before you start.
- Statistical analysis of neuroimaging data, supervised by Mattias Villani.
- Evaluation of support vector machines for analysis of genome-wide DNA data, supervised by Patrik Waldmann.
- Analysis of predictive power of data mining algorithms with embedded monotonicity constraints, supervised by Oleg Sysoev.
- Various topics on probabilistic graphical models such as Bayesian networks and chain graphs, supervised by Jose M. Pena.
Page responsible: Jos?M Pena
Last updated: 2015-06-24