The exam consists in two assignments, one on the first part(regression, tree, neural nets) and the second part (unsupervised learning). For both you must prepare a writing report using one or more techniques and comparing their performance on one or more data set chosen by the student. A brief oral presentation of the reports will be asked.
Each report must contain:
- short abstract: what are your going to present in the report
- statement of the problem/goal of the analysis and description of the data set(s)
- list of three to five findings/keypoints
- the analysis with wise commentary
- (optional) theoretical background of the used methods
- conclusions(should include the findings/keypoints)
- the Appendix, containing all the R code
Notice:
- The paper length is irrelevant provided that the content is correct.
- No R code in the main text. The R code must be confined to the appendix
- The report should be prepared in PDF only