Comparison of Selection Criteria for Model Selection of Support Vector Machine on Physiological Data with Inter-Subject Variance

• Published in: Applied sciences Vol. 12; no. 3; p. 1749
• Main Authors: Choi, Minho, Jeong, Jae Jin
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2022
• Subjects: Algorithms; Classification; Datasets; inter-subject variance; model selection; Performance evaluation; physiological data; Physiology; support vector machine; Support vector machines

Support vector machines (SVMs) utilize hyper-parameters for classification. Model selection (MS) is an essential step in the construction of the SVM classifier as it involves the identification of the appropriate parameters. Several selection criteria have been proposed for MS, but their usefulness...