Abstract
Rough set based rule generation methods need discretization of the continuous values. However, most existing discretization methods cause inconsistencies. In this paper, we propose an algorithm that can eliminate the inconsistencies caused during the course of discretization. The algorithm can be integrated into the discaretization algorithms that cannot avoid causing inconsistencies to eliminate the inconsistencies. Three data experimental results show that the algorithm is available.
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References
Dougherty, J., Kohavi, R., Sahami, M.: Supervised and unsupervised discretization of continuous features. In: Proc. of the 12th International Conference on Machine Learning, pp. 194–202 (1995)
Kononenko, I.: Naive Bayes classifier and continuous attributes Informatica, vol. 16, pp. 1–8 (1992)
Kononenko, I.: Inductive and Bayesian learning in medical diagnosis. Appl. Artif. Intell. 7, 317–337 (1993)
Fayyad, U.M.: On the Induction of Decision Trees for Multiple Concept Learning. Ph.D. thesis, University of Michigan (1991)
Fayyad, U.M., Irani, K.: Multiinterval discretization of continuous-valued attributes for classification learning. In: Proc. of the 12th International Joint Conference on Artificial Intelligence, pp. 1022–1027 (1993)
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© 2006 Springer-Verlag Berlin Heidelberg
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Honghai, F., Baoyan, L., LiYun, H., Bingru, Y., Yumei, C., Shuo, Z. (2006). An Algorithm for Eliminating the Inconsistencies Caused During Discretization. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11892960_18
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DOI: https://doi.org/10.1007/11892960_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46535-5
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