Differential evolution and particle swarm optimisation in partitional clustering
Computational Statistics & Data Analysis
Regression model selection using genetic algorithms
NN'10/EC'10/FS'10 Proceedings of the 11th WSEAS international conference on nural networks and 11th WSEAS international conference on evolutionary computing and 11th WSEAS international conference on Fuzzy systems
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In this paper, we describe some evolutionary approaches based on genetic algorithms to deal with the statistical model selection problem using completely data-driven algorithms. First, we propose an approach to select multivariate linear regression models as well as to build ARMA time-series models. Then we introduce a methodology to tackle the clustering problem in a model-based framework. We report the results from several applications and from simulated data sets, and we compare the evolutionary approaches with some classical ones.