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
