Abstract
Firefly Algorithm is a newly proposed method with potential application on several real world problems, such as variable selection problem. This paper presents a Multiobjective Firefly Algorithm (MOFA) for variable selection in multivariate calibration models. The main objective is to propose an optimization to reduce the error value prediction of the property of interest, as well as reducing the number of variables selected. Based on the results obtained, it is possible to demonstrate that our proposal may be a viable alternative in order to deal with conflicting objective-functions. Additionally, we compare MOFA with traditional algorithms for variable selection and show that it is a more relevant contribution for the variable selection problem.
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References
Soares, A.S., de Lima, T.W., Soares, F.A.A.M.N., Coelho, C.J., Federson, F.M., Delbem, A.C.B., Van Baalen, J.: Mutation-based compact genetic algorithm for spectroscopy variable selection in determining protein concentration in wheat grain. Electronics Letters 50, 932–934 (2014)
Lucena, D.V., Soares, A.S., Soares, T.W., Coelho, C.J.: Multi-Objective Evolutionary Algorithm NSGA-II for Variables Selection in Multivariate Calibration Problems. International Journal of Natural Computing Research 3, 43–58 (2012)
Martens, H.: Multivariate Calibration. John Wiley & Sons (1991)
Paula, L.C.M., Soares, A.S., Soares, T.W., Delbem, A.C.B., Coelho, C.J., Filho, A.R.G.: Parallelization of a Modified Firefly Algorithm using GPU for Variable Selection in a Multivariate Calibration Problem. International Journal of Natural Computing Research 4, 31–42 (2014)
Hibon, M., Makridakis, S.: Evaluating Accuracy (or Error) Measures. INSEAD (1995)
Arajo, M.C.U., Saldanha, T.C., Galvo, R.K., Yoneyama, T.: The successive projections algorithm for variable selection in spectroscopic multicomponent analysis. Chemometrics and Intelligent Laboratory Systems 57, 65–73 (2001)
Ramsey, P.H.: Significance probabilities of the wilcoxon signed-rank test. Journal of Nonparametric Statistics 2, 133–153 (1993)
Yang, X.S.: Multiobjective firefly algorithm for continuous optimization. Engineering with Computers 29, 175–184 (2013)
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© 2015 Springer International Publishing Switzerland
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de Paula, L.C.M., da Silva Soares, A. (2015). Multiobjective Firefly Algorithm for Variable Selection in Multivariate Calibration. In: Pereira, F., Machado, P., Costa, E., Cardoso, A. (eds) Progress in Artificial Intelligence. EPIA 2015. Lecture Notes in Computer Science(), vol 9273. Springer, Cham. https://doi.org/10.1007/978-3-319-23485-4_27
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DOI: https://doi.org/10.1007/978-3-319-23485-4_27
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