A Texture-based Classification Method for Proteins in Two-Dimensional Electrophoresis Gel Images - A Feature Selection Method using Support Vector Machines and Genetic Algorithms

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
M. A. Duarte-Mermoud ◽  
N. H. Beltrán ◽  
S. A. Salah

Recently, a new crossover technique for genetic algorithms has been proposed. The technique, called probabilistic adaptive crossover (PAX), includes the estimation of the probability distribution of the population, storing the information regarding the best and the worst solutions of the problem being solved in a probability vector. The use of the proposed technique to face Chilean wine classification based on chromatograms obtained from an HPLC is reported in this paper. PAX is used in the first stage as the feature selection method and then support vector machines (SVM) and linear discriminant analysis (LDA) are used as classifiers. The results are compared with those obtained using the uniform (discrete) crossover standard technique and a variant of PAX called mixed crossover.


2014 ◽  
Vol 6 (12) ◽  
pp. 12005-12036 ◽  
Author(s):  
Eleni Dragozi ◽  
Ioannis Gitas ◽  
Dimitris Stavrakoudis ◽  
John Theocharis

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