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Fifth Mexican International Conference in Computer Science (ENC'04)
A Method Based on Genetic Algorithms and Fuzzy Logic to Induce Bayesian Networks
Colima, M?xico
September 20-September 24
ISBN: 0-7695-2160-6
Manuel Martínez Morales, Universidad Veracruzana
Ramiro Garza Domínguez, Universidad Veracruzana
Nicandro Cruz Ramírez, Universidad Veracruzana
Alejandro Guerra Hernández, Universidad Veracruzana
José Luis Jiménez Andrade, Universidad Veracruzana
A method to induce bayesian networks from data to over-come some limitations of other learning algorithms is proposed. One of the main features of this method is a metric to evaluate bayesian networks combining different quality criteria. A fuzzy system is proposed to enable the combination of different quality metrics. In this fuzzy system a metric of classification is also proposed, a criterium that is not often used to guide the search while learning bayesian networks. Finally, the fuzzy system is integrated to a genetic algorithm, used as a search method to explore the space of possible bayesian networks, resulting in a robust and flexible learning method with performance in the range of the best learning algorithms of bayesian networks developed up to now.
Citation:
Manuel Martínez Morales, Ramiro Garza Domínguez, Nicandro Cruz Ramírez, Alejandro Guerra Hernández, José Luis Jiménez Andrade, "A Method Based on Genetic Algorithms and Fuzzy Logic to Induce Bayesian Networks," enc, pp.176-180, Fifth Mexican International Conference in Computer Science (ENC'04), 2004
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