Fuzzy classification of mortality by infection of severe burnt patients using multiobjective evolutionary algorithms

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Abstract

The classification of survival in severe burnt patients is an on-going problem. In this paper we propose a multiobjective optimisation model with constraints to obtain fuzzy classification models based on the criteria of accuracy and interpretability. We also describe a multiobjective evolutionary approach for fuzzy classification based on data with real and discrete attributes. This approach is evaluated using three different evolutive schemas: pre-selection with niches, NSGA-II and ENORA. The results are compared as regards efficacy by statistical techniques. © 2009 Springer Berlin Heidelberg.

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Jiménez, F., Sánchez, G., Juárez, J. M., Alcaraz, J. M., & Sánchez, J. F. (2009). Fuzzy classification of mortality by infection of severe burnt patients using multiobjective evolutionary algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5601 LNCS, pp. 447–456). https://doi.org/10.1007/978-3-642-02264-7_46

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