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The problem of selecting variables in data-mining can be modelled as an optimisation problem involving multiple objectives which must be simultaneously optimised. This contribution proposes a multiple objective optimisation model for the problem of selecting variables applicable to the classification of mortality in patients from a hospital burns unit. The evolutionary multiobjective algorithm NSGA-II was adapted to resolve the proposed multiobjective optimisation model proposed and the results obtained were compared with those obtained with a battery of algorithms intended for selecting variables included in the Weka data-mining platform. The comparison underlines the efficacy and suitability of the proposed model and of the use of multiobjective evolutionary computation in this type of problem.

ATTRIBUTE SELECTION BY MULTIOBJECTIVE EVOLUTIONARY COMPUTATION APPLIED TO MORTALITY FROM INFECTION IN SEVERE BURNS PATIENTS