Recommendation system

As an academic project I worked in the development using the python programming language of a recommendation system which has as an entry the preferences and class of several users in a web site.

I used the naive Bayes algorithm when we suppose all the variables independent, with the maximum likelihood and the priori knowledge approaches to determinate the probabilities of belonging for each class in such a way that the system could to predict the class of a new user who doesn’t have all the preferences and furthermore to predict the preferences in absence.

I coded as well an approach using the tree-augmented naive model (TAN) algorithm building a Bayesian network which we learned the mutual information between the variables to predict the class which a user belongs.

Paris - France, January 2013