| Title | Claps | Level | Year | L/Y |
|---|---|---|---|---|
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Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification
7 auth. C. Fernandez-Lozano, C. Canto, M. Gestal, J. M. Andrade‐Garda, J. Rabuñal, J. Dorado, ...
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…
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.
Published in
TheScientificWorldJournal
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0
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4 | 2013 |
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