In this paper a data miner based on the learning
automata is proposed and is called LA-miner. The LA-miner extracts
classification rules from data sets automatically. The proposed
algorithm is established based on the function optimization using
learning automata. The experimental results on three benchmarks
indicate that the performance of the proposed LA-miner is
comparable with (sometimes better than) the Ant-miner (a data miner
algorithm based on the Ant Colony optimization algorithm) and CNZ
(a well-known data mining algorithm for classification).
[1] B. J. Oommen, E.V. de St. Criox, "Graph partitioning using learning
automata," IEEE Trans. Comput., vol. 45, pp. 195-208, 1996.
[2] H. Beigy, M.R. Meybodi, "Backpropagation algorithm adaptation
parameters using learning automata," Int. J. Neural Syst., vol. 11,
pp.219-228, 2001.
[3] S.H. Zahiri, "Learning automata based classifier," Pattern Recognition
Letters, vol. 9, pp.40-48, 2008.
[4] R.S. Parepinelli, H.S. Lopes, A. Freitas, "An ant colony algorithm for
classification rules discovery," IEEE Trans. Evol. Comp., vol. 6, No.4,
pp.321-332, 2002.
[5] P. Clark, T.Niblet, "The CNZ induction algorithm," Mach. Learn., vol.3,
no.4, pp.261-283, 1989.
[1] B. J. Oommen, E.V. de St. Criox, "Graph partitioning using learning
automata," IEEE Trans. Comput., vol. 45, pp. 195-208, 1996.
[2] H. Beigy, M.R. Meybodi, "Backpropagation algorithm adaptation
parameters using learning automata," Int. J. Neural Syst., vol. 11,
pp.219-228, 2001.
[3] S.H. Zahiri, "Learning automata based classifier," Pattern Recognition
Letters, vol. 9, pp.40-48, 2008.
[4] R.S. Parepinelli, H.S. Lopes, A. Freitas, "An ant colony algorithm for
classification rules discovery," IEEE Trans. Evol. Comp., vol. 6, No.4,
pp.321-332, 2002.
[5] P. Clark, T.Niblet, "The CNZ induction algorithm," Mach. Learn., vol.3,
no.4, pp.261-283, 1989.
@article{"International Journal of Information, Control and Computer Sciences:55233", author = "M. R. Aghaebrahimi and S. H. Zahiri and M. Amiri", title = "Data Mining Using Learning Automata", abstract = "In this paper a data miner based on the learning
automata is proposed and is called LA-miner. The LA-miner extracts
classification rules from data sets automatically. The proposed
algorithm is established based on the function optimization using
learning automata. The experimental results on three benchmarks
indicate that the performance of the proposed LA-miner is
comparable with (sometimes better than) the Ant-miner (a data miner
algorithm based on the Ant Colony optimization algorithm) and CNZ
(a well-known data mining algorithm for classification).", keywords = "Data mining, Learning automata, Classification
rules, Knowledge discovery.", volume = "3", number = "1", pages = "96-4", }