Attribute Selection by Multiobjective Evolutionary Computation Applied to Mortality From Infection in Severe Burns Patients

Abstract

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.