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

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 mac...

Descripción completa

Detalles Bibliográficos
Autores principales: Fernandez-Lozano, C., Canto, C., Gestal, M., Andrade-Garda, J. M., Rabuñal, J. R., Dorado, J., Pazos, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3874306/
https://www.ncbi.nlm.nih.gov/pubmed/24453933
http://dx.doi.org/10.1155/2013/982438
_version_ 1782297213838295040
author Fernandez-Lozano, C.
Canto, C.
Gestal, M.
Andrade-Garda, J. M.
Rabuñal, J. R.
Dorado, J.
Pazos, A.
author_facet Fernandez-Lozano, C.
Canto, C.
Gestal, M.
Andrade-Garda, J. M.
Rabuñal, J. R.
Dorado, J.
Pazos, A.
author_sort Fernandez-Lozano, C.
collection PubMed
description 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.
format Online
Article
Text
id pubmed-3874306
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Hindawi Publishing Corporation
record_format MEDLINE/PubMed
spelling pubmed-38743062014-01-16 Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification Fernandez-Lozano, C. Canto, C. Gestal, M. Andrade-Garda, J. M. Rabuñal, J. R. Dorado, J. Pazos, A. ScientificWorldJournal Research Article 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. Hindawi Publishing Corporation 2013-12-10 /pmc/articles/PMC3874306/ /pubmed/24453933 http://dx.doi.org/10.1155/2013/982438 Text en Copyright © 2013 C. Fernandez-Lozano et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Fernandez-Lozano, C.
Canto, C.
Gestal, M.
Andrade-Garda, J. M.
Rabuñal, J. R.
Dorado, J.
Pazos, A.
Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification
title Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification
title_full Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification
title_fullStr Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification
title_full_unstemmed Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification
title_short Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification
title_sort hybrid model based on genetic algorithms and svm applied to variable selection within fruit juice classification
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3874306/
https://www.ncbi.nlm.nih.gov/pubmed/24453933
http://dx.doi.org/10.1155/2013/982438
work_keys_str_mv AT fernandezlozanoc hybridmodelbasedongeneticalgorithmsandsvmappliedtovariableselectionwithinfruitjuiceclassification
AT cantoc hybridmodelbasedongeneticalgorithmsandsvmappliedtovariableselectionwithinfruitjuiceclassification
AT gestalm hybridmodelbasedongeneticalgorithmsandsvmappliedtovariableselectionwithinfruitjuiceclassification
AT andradegardajm hybridmodelbasedongeneticalgorithmsandsvmappliedtovariableselectionwithinfruitjuiceclassification
AT rabunaljr hybridmodelbasedongeneticalgorithmsandsvmappliedtovariableselectionwithinfruitjuiceclassification
AT doradoj hybridmodelbasedongeneticalgorithmsandsvmappliedtovariableselectionwithinfruitjuiceclassification
AT pazosa hybridmodelbasedongeneticalgorithmsandsvmappliedtovariableselectionwithinfruitjuiceclassification

Ejemplares similares