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Improved Classification Performance of Support Vector Machine Technique Using the Genetic Algorithm
˜Al-œRafidain journal for computer sciences and mathematics
In this research, the genetic algorithm was proposed as a method to find the parameters of support vector machine, specifically the σ and c parameters for kernel and the hyperplane respectively. Based on the Least squares method, the fitness function was built in the genetic algorithm to find the optimal values of the parameters in the proposed method. The proposed method showed better and more efficient results than the classical method of support vector machine which adopts the default ordoi:10.33899/csmj.2018.163581 fatcat:mbqcvo54szhd7jhawmxt2kswye