Triangulation of Bayesian networks with recursive estimation of distribution algorithms

Triangulation of Bayesian networks with recursive estimation of distribution algorithms

Unsupervised Learning of Bayesian Networks Via Estimation of Distribution Algorithms

This paper proposes the use of estimation of distribution algorithms for unsupervised learning of Bayesian networks. The empirical results reported for one of the simplest estimation of distribution algorithms confirm the ability of this approach to induce models that show (i) similar fitness of the learning data to that of the original models, (ii) satisfactory generalization of the learning d...

Learning Bayesian Networks In The Space Of Orderings With Estimation Of Distribution Algorithms

The search for the optimal ordering of a set of variables in order to solve a computational problem is a difficulty that can appear in several circumstances. One of these situations is the automatic learning of a network structure, for example, a Bayesian Network structure (BN) starting from a dataset. Searching in the space of structures is often unmanageable, especially if the number of varia...

Pruning Neural Networks with Distribution Estimation Algorithms

This paper describes the application of four evolutionary algorithms to the pruning of neural networks used in classification problems. Besides of a simple genetic algorithm (GA), the paper considers three distribution estimation algorithms (DEAs): a compact GA, an extended compact GA, and the Bayesian Optimization Algorithm. The objective is to determine if the DEAs present advantages over the...

Structure Learning of Bayesian Networks by Estimation of Distribution Algorithms with Transpose Mutation

Estimation of distribution algorithms (EDAs) constitute a new branch of evolutionary optimization algorithms that were developed as a natural alternative to genetic algorithms (GAs). Several studies have demonstrated that the heuristic scheme of EDAs is effective and efficient for many optimization problems. Recently, it has been reported that the incorporation of mutation into EDAs increases t...