Abstract
A parallel ant colony algorithm for mining the classification rules is presented. By preprocessing classification information on databases and combining ACO with parallel strategies, our algorithm could extract classification rules efficiently in parallel. Experimental results on several benchmark datasets show that our algorithm can discover classification rules more quickly with better accuracy, simplicity than other methods such as improved Ant-Miner algorithm and C4.5 based on well known decision tree algorithm.
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References
Chang, S.-Y., Lin, C.-R., Chang, C.-T.: A fuzzy diagnosis approach using dynamic fault trees. Chemical Engineering Science 57(15), 2971–2985 (2002)
Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Francisco (1993)
Romăo, W., Freitas, A.A., de Gimenes, I.M.S.: Discovering interesting knowledge from a science and technology database with a genetic algorithm. Applied Soft Computing 4, 21–137 (2004)
Dorigo, M., Gambardella, L.M.: Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans. on Evolutionary Computation 1(1), 53–66 (1997)
Parepinelli, R.S., Lopes, H.S., Freitas, A.: An Ant Colony Algorithm for Classification Rule Discovery. In: Newton, H.A.a.R.S.a.C. (ed.) Data Mining: Heuristic Approach. Idea Group Publishing, USA (2002)
Shelokar, P.S., Jayaraman, V.K., Kulkarni, B.D.: An ant colony classifier system: application to some process engineering problems. Computers and Chemical Engineering 28, 1577–1584 (2004)
Liu, B., Abbass, H.A., McKay, B.: Density-based Heuristic for Rule Discovery with Ant-Miner. In: The 6th Australia-Japan Joint Workshop on Intelligent and Evolutionary System, pp. 180–184 (2002)
Jordan, H.F., Alaghband, G.: Foundations of Parallel Processing. Prentice Hall, Englewood Cliffs (2003)
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© 2005 Springer-Verlag Berlin Heidelberg
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Chen, L., Tu, L. (2005). Parallel Mining for Classification Rules with Ant Colony Algorithm. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_37
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DOI: https://doi.org/10.1007/11596448_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30818-8
Online ISBN: 978-3-540-31599-5
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