This module deals with mathematical methods specific to large dimensions: large numbers of variables and/or individuals. The methods are based on general statistical models but which rely on particular hypotheses: weak effective dimension, additivity, etc. The following themes will be studied :
- Large dimension regression
- Bayesian networks
- Optimisation for large dimension
| On completion of the unit, the student will be capable of: | Classification level | Priority |
|---|---|---|
| Understanding specific methods for handling cases of large numbers of variables and /or individuals | 2. Understand | Important |
| Applying some basic techniques such as large dimension regression | 3. Apply | Essential |
| Analysing real case studies | 4. Analyse | Important |
| Percentage ratio of individual assessment | Percentage ratio of group assessment | ||||
|---|---|---|---|---|---|
| Written exam: | % | Project submission: | % | ||
| Individual oral exam: | % | Group presentation: | % | ||
| Individual presentation: | % | Group practical exercise: | % | ||
| Individual practical exercise: | % | Group report: | 50 | % | |
| Individual report: | 50 | % | |||
| Other(s): % | |||||
| Type of teaching activity | Content, sequencing and organisation |
|---|