Support Vector Machine: Applications and Improvements Using Evolutionary Algorithms

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Author(s)
Mehne, Seyed Hamed Hashemi
Mirjalili, Seyedali
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Mirjalili, Seyedali
Faris, Hossam
Aljarah, Ibrahim
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2020
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Abstract

A description of the theory and the mathematical base of support vector machines with a survey on its applications is first presented in this chapter. Then, a method for obtaining nonlinear kernel of support vector machines is proposed. The proposed method uses the gray wolf optimizer for solving the corresponding nonlinear optimization problem. A sensitivity analysis is also performed on the parameter of the model to tune the resulting classifier. The method has been applied to a set of experimental data for diabetes mellitus diagnosis. Results show that the method leads to a classifier which distinguished healthy and patient cases with 87.5% of accuracy.

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Evolutionary Machine Learning Techniques
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Subject
Machine learning
Artificial intelligence
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Mehne, SHH; Mirjalili, S, Support Vector Machine: Applications and Improvements Using Evolutionary Algorithms, Evolutionary Machine Learning Techniques, 2020, pp. 35-50
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