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Alves, Roberto T.; Delgado, Myriam; Lopes, Heitor S.; Freitas, Alex A. (2004)
Publisher: Springer-Verlag
Languages: English
Types: Unknown
Subjects: QA76
This work proposes a classification-rule discovery algorithm integrating artificial immune systems and fuzzy systems. The algorithm consists of two parts: a sequential covering procedure and a rule evolution procedure. Each antibody (candidate solution) corresponds to a classification rule. The classification of new examples (antigens) considers not only the fitness of a fuzzy rule based on the entire training set, but also the affinity between the rule and the new example. This affinity must be greater than a threshold in order for the fuzzy rule to be activated, and it is proposed an adaptive procedure for computing this threshold for each rule. This paper reports results for the proposed algorithm in several data sets. Results are analyzed with respect to both predictive accuracy and rule set simplicity, and are compared with C4.5rules, a very popular data mining algorithm.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • 2. Witten, I. H., Frank, E.: Data Mining: Pratical Machine Learning Tools and Techniques with Java Implementation. Morgan Kaufmann, San Mateo (2000)
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    • 10. Freitas, A.A., Timmis, J.: Revisiting the Foundations of Artificial Immune Systems: a Problem-oriented Perspective. Proc. 2nd International Conference on Artificial Immune Systems. Lecture Notes in Computer Science, Vol. 2787. Springer-Verlag, Berlin (2003) 229-241
    • 11. Nasaroui, O., Gonzales, F., Dasgupta, D.: The Fuzzy Artificial Immune System: motivations, Basic Concepts, and Application to Clustering and Web Profiling. Proceedings of IEEE International Conference on Fuzzy Systems (2002) 711-716
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    • 13. Back, T., Fogel, D.B., and Michalewicz, T. (Eds.): Evolutionary Computation, Vol. 1. IoP Publishing, Oxford, UK (2000)
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    • 16. Parpinelli, R.S., Lopes, H.S., Freitas, A.A.: Data Mining With an Ant Colony Optimization Algorithm. IEEE T. Evol. Comput. 6:4 (2002) 321-332
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