Abstract. We present the Acyclic Bayesian Net Generator, a new approach to learn the structure of a Bayesian network using genetic algorithms. Due to the encoding mechanism, acycli...
A method to induce bayesian networks from data to overcome some limitations of other learning algorithms is proposed. One of the main features of this method is a metric to evalua...
Bayesian Network structures with a maximum in-degree of k can be approximated with respect to a positive scoring metric up to an factor of 1/k. Key words: approximation algorithm,...
To improve the recovery of gene-gene and marker-gene (eQTL) interaction networks from microarray and genetic data, we propose a new procedure for learning Bayesian networks. This a...
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...