TY - GEN
T1 - Structure learning of bayesian networks using a semantic genetic algorithm-based approach
AU - Shetty, Sachin
AU - Song, Min
PY - 2005
Y1 - 2005
N2 - A Bayesian network model is a popular technique for data mining due to its intuitive interpretation. This paper presents a semantic genetic algorithm (SGA) to learn a complete qualitative structure of a Bayesian network from a database. SGA builds on recent advances in the field and focuses on the generation of initial population, crossover, and mutation operators. Particularly, we introduce two semantic crossover and mutation operators that aid in faster convergence of the SGA. The crossover and mutation operators in SGA incorporate the semantic of the Bayesian network structures to learn the structure with very minimal errors. SGA has been proved to perform better than existing classical genetic algorithms for learning Bayesian networks. We present empirical results to prove the fast convergence of SGA and the predictive power of the obtained Bayesian network structures.
AB - A Bayesian network model is a popular technique for data mining due to its intuitive interpretation. This paper presents a semantic genetic algorithm (SGA) to learn a complete qualitative structure of a Bayesian network from a database. SGA builds on recent advances in the field and focuses on the generation of initial population, crossover, and mutation operators. Particularly, we introduce two semantic crossover and mutation operators that aid in faster convergence of the SGA. The crossover and mutation operators in SGA incorporate the semantic of the Bayesian network structures to learn the structure with very minimal errors. SGA has been proved to perform better than existing classical genetic algorithms for learning Bayesian networks. We present empirical results to prove the fast convergence of SGA and the predictive power of the obtained Bayesian network structures.
KW - Bayesian networks
KW - Data mining
KW - Genetic algorithms
KW - Structure learning
UR - http://www.scopus.com/inward/record.url?scp=33745697937&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33745697937&partnerID=8YFLogxK
U2 - 10.1109/ITRE.2005.1503164
DO - 10.1109/ITRE.2005.1503164
M3 - Conference contribution
AN - SCOPUS:33745697937
SN - 0780389328
SN - 9780780389328
T3 - ITRE 2005 - 3rd International Conference on Information Technology: Research and Education - Proceedings
SP - 454
EP - 458
BT - ITRE 2005 - 3rd International Conference on Information Technology
T2 - ITRE 2005 - 3rd International Conference on Information Technology: Research and Education
Y2 - 27 June 2005 through 30 June 2005
ER -