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http://hdl.handle.net/2183/19747

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

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Identifiers

URI: http://hdl.handle.net/2183/19747

Publication date

2013-10-21

Authors

Canto, C.

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Other responsabilities

Journal Title

Bibliographic citation

Fernández-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;2013

Type of academic work

Academic degree

Abstract

[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.

Description

Research article

Keywords

Algorithms Beverages Fruit Malus Neural networks (Computer) Support vector machines

Editor version

http://dx.doi.org/10.1155/2013/982438

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Atribución 3.0 España

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Investigación (FIC)
Atribución 3.0 España

Except where otherwise noted, this item's license is described as Atribución 3.0 España