Bayesian Networks Optimization Based on Induction Learning Techniques

Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learning method that optimizes the bayesian networks applied to classification, using a hybrid method of learning that combines the advantages of the induction techniques of the decision trees with those of the bayesian networks.

• Type: Conference
• Year: 2008
• Where: IFIP12
• Authors: Paola Britos, Pablo Felgaer, Ramón García-Martínez
• Keywords: Automatic Learning Method, Bayesian Networks, IFIP12 2008, Information Technology, Learning Process