The evaluation of the prediction of the model on the test set showed the validity of the approach: the model had one of the best performances of the challenge. As a note, the performances of the model on the test set are higher than the one obtained with crossvalidation on the training set (e.g. F-measure metrics are 71.26% and 71.15%, respectively).