Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection Within Fruit Juice Classification

Fernández-Lozano, CarlosCanto, C.Gestal, M.Andrade-Garda, José ManuelRabuñal, Juan R.Dorado, JuliánPazos, A.2017-11-142017-11-142013-10-21Fernández-Lozano C, Canto C, Gestal M, et al. Hybrid model based on genetic algorithms and SVM applied to variable selection within fruit juice classification. Sci World J. 2013;20131537-744X2356-6140http://hdl.handle.net/2183/19747Research article[Abstract] Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected.engAtribución 3.0 Españahttp://creativecommons.org/licenses/by/3.0/es/AlgorithmsBeveragesFruitMalusNeural networks (Computer)Support vector machinesHybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection Within Fruit Juice Classificationjournal articleopen access