This paper introduces a genetic algorithm able to combine different classifiers based on different distance functions. The use of a genetic algorithm is motivated by the fact that the combination phase is based on the optimization of a vote strategy. The method has been applied to the classification of four types of biological cells, results show an improvement of the recognition rate using the genetic algorithm combination strategy compared with the recognition rate of each single classifier.
LO BOSCO, G. (2007). An integrated fuzzy cells-classifier. IMAGE AND VISION COMPUTING, 25, 214-219 [10.1016/j.imavis.2006.01.031].
An integrated fuzzy cells-classifier
LO BOSCO, Giosue'
2007-01-01
Abstract
This paper introduces a genetic algorithm able to combine different classifiers based on different distance functions. The use of a genetic algorithm is motivated by the fact that the combination phase is based on the optimization of a vote strategy. The method has been applied to the classification of four types of biological cells, results show an improvement of the recognition rate using the genetic algorithm combination strategy compared with the recognition rate of each single classifier.
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