Your browser doesn't support javascript.
loading
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.
Affiliation
  • Fernandez-Lozano C; Information and Communications Technologies Department, Faculty of Computer Science, University of A Coruña, Campus Elviña s/n, 15071, A Coruña, Spain.
  • Canto C; Information and Communications Technologies Department, Faculty of Computer Science, University of A Coruña, Campus Elviña s/n, 15071, A Coruña, Spain.
  • Gestal M; Information and Communications Technologies Department, Faculty of Computer Science, University of A Coruña, Campus Elviña s/n, 15071, A Coruña, Spain.
  • Andrade-Garda JM; Analytical Chemistry Department, Faculty of Sciences, University of A Coruña, Campus da Zapateira s/n, 15008, A Coruña, Spain.
  • Rabuñal JR; Information and Communications Technologies Department, Faculty of Computer Science, University of A Coruña, Campus Elviña s/n, 15071, A Coruña, Spain.
  • Dorado J; Information and Communications Technologies Department, Faculty of Computer Science, University of A Coruña, Campus Elviña s/n, 15071, A Coruña, Spain.
  • Pazos A; Information and Communications Technologies Department, Faculty of Computer Science, University of A Coruña, Campus Elviña s/n, 15071, A Coruña, Spain.
ScientificWorldJournal ; 2013: 982438, 2013.
Article in En | MEDLINE | ID: mdl-24453933
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.
Subject(s)
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Beverages / Algorithms / Neural Networks, Computer / Malus / Support Vector Machine / Fruit Type of study: Prognostic_studies Language: En Journal: ScientificWorldJournal Journal subject: MEDICINA Year: 2013 Document type: Article Affiliation country: Country of publication:
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Beverages / Algorithms / Neural Networks, Computer / Malus / Support Vector Machine / Fruit Type of study: Prognostic_studies Language: En Journal: ScientificWorldJournal Journal subject: MEDICINA Year: 2013 Document type: Article Affiliation country: Country of publication: