The Effects of Kernel Functions and Optimal Hyperparameter Selection on Support Vector Machines
Support Vector Machine (SVM) is a supervised machine learning method used for classification and regression. It is based on the Vapnik-Chervonenkis (VC) theory and Structural Risk Minimization (SRM) principle. Thanks to its strong theoretical background, SVM exhibits a high performance compared to m...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Naim Çağman
2021-03-01
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| Series: | Journal of New Theory |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/en/download/article-file/1564998 |