Parameter determination of support vector machine using scatter search approach

Afif, Mohammed H.; Hedar, Abdel-Rahman; Hamid, Taysir H. Abdel; Mahdy, Yousef B.

doi:10.1109/iccta.2012.6523566

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2017

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“…Ao et al [30] proposed a SVM parameter optimization method based on artificial chemical reaction optimization algorithm (ACROA) to diagnose roller bearing faults. Afif et al [31] used a scatter search approach to find near optimal values of the SVM parameters. Kartelj et al [32] introduced an electromagnetism-like (EM) approach for solving the problem of parameter tuning in the SVM.…”

Section: Other Optimization Algorithmsmentioning

confidence: 99%

A Brief Overview on Parameter Optimization of Support Vector Machine

Cao¹,

Yu²,

Cheng³

2017

dtmse

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Support vector machine (SVM) has been successfully applied in classification and regression problems. But it is very sensitive to the selection of parameters. The fundamental principles of SVM are analyzed firstly. The main optimization methods and achievements for SVM parameters are introduced. And the popular fitness functions used for the parameter optimization of SVM are described. The objective of this paper is to provide readers a brief overview of the recent advances for parameter optimization of SVM and enable them to develop and implement new optimization strategies for SVM-related research at their disposal.

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Section: Other Optimization Algorithmsmentioning

confidence: 99%