Abstract
In this paper a methodology using evolutionary algorithms is introduced for the optimization of fuzzy classifiers based on B-splines. The proposed algorithm maximizes the performance and minimizes the size of the classifier. On a well-known classification problem the algorithm performs an input selection over 9 observed characteristics yielding in a statement which attributes are important with respect to diagnose malignant or benign type of cancer.
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References
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Renners, I., Grauel, A., Saavedra, E. (2001). Methodology for Optimizing Fuzzy Classifiers Based on Computational Intelligence. In: Reusch, B. (eds) Computational Intelligence. Theory and Applications. Fuzzy Days 2001. Lecture Notes in Computer Science, vol 2206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45493-4_42
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DOI: https://doi.org/10.1007/3-540-45493-4_42
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42732-2
Online ISBN: 978-3-540-45493-9
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