Comments on “Imprecise probability models for learning multinomial distributions from data. Applications to learning credal networks” by Andrés R. Masegosa and Serafín Moral

We briefly overview the problem of learning probabilities from data using imprecise probability models that express very weak prior beliefs. Then we comment on the new contributions to this question given in the paper by Masegosa and Moral and provide some insights about the performance of their models in data mining experiments of classification.