Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification
oleh: C. Fernandez-Lozano, C. Canto, M. Gestal, J. M. Andrade-Garda, J. R. Rabuñal, J. Dorado, A. Pazos
| Format: | Article |
|---|---|
| Diterbitkan: | Wiley 2013-01-01 |
Deskripsi
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.