期刊
APPLIED SOFT COMPUTING
卷 49, 期 -, 页码 56-70出版社
ELSEVIER
DOI: 10.1016/j.asoc.2016.07.017
关键词
Classification; Utility function; UTADIS method; Genetic algorithm; Particle swarm optimization algorithm
In this study, a new multi-criteria classification technique for nominal and ordinal groups is developed by expanding the UTilites Additives DIScriminantes (UTADIS) method with a polynomial of degree T which is used as the utility function rather than using a piecewise linear function as an approximation of the utility function of each attribute. We called this method as PUTADIS. The objective is calculating the coefficients of the polynomial and the threshold limit of classes and weight of attributes such that it minimizes the number of misclassification error. Estimation of unknown parameters of the problem is calculated by using a hybrid algorithm which is a combination of particle swarm optimization algorithm (PSO) and Genetic Algorithm (GA). The results obtained by implementing the model on different datasets and comparing its performance with other previous methods show the high efficiency of the proposed method. (C) 2016 Elsevier B.V. All rights reserved.
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