Fuzzy Classification of Mortality by Infection of Severe Burnt Patients Using Multiobjective Evolutionary Algorithms

Authors:
F. Jiménez;G. Sánchez;J. M. Juárez;J. M. Alcaraz;J. F. Sánchez
Affiliations:
Dept. Ingeniería de la Información y las Comunicaciones, Universidad de Murcia,;Dept. Ingeniería de la Información y las Comunicaciones, Universidad de Murcia,;Dept. Ingeniería de la Información y las Comunicaciones, Universidad de Murcia,;Dept. Ingeniería de la Información y las Comunicaciones, Universidad de Murcia,;Dept. Ingeniería de la Información y las Comunicaciones, Universidad de Murcia,
Venue:
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
Year:
2009

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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.