Everything here is under development, so it may change over time. You are not looking at the final version of this project.

In this repository there will be stored all the material related to the analysis of (my) tastes on films. According to my current plans, different working methods will be addressed. My ultimate goal is to practice, have fun, and maybe draw some interesting conclusions.

All the code and the useful files will be stored in folders according to the different parts of the analysis. In each folder there will also be a pdf file (automatically generated by R Markdown) with the comments of the obtained results.

• 0 - Preface: description of the problem and of the dataset.

• 1 - Web Scraping with Python: how the dataset has been built.

• 2 - Cluster analysis with R: k-means, hierarchical clustering, PAM, mixture models, robust clustering methods and others.

• 3 - Variable selection and dimension reduction with R: best subset selection, forward selection, backward elimination, Lasso, principal components regresion, partial least squares regression, index construction and others.

• 4 - Comparison of the results and final considerations.

• [...]

For further informations, don’t hesitate to contact me or to report an issue here!