Kernel Parameter Selection for Support Vector Machine Classification
Parameter selection for kernel functions is important to the robust classification performance of a support vector machine (SVM). This paper introduces a parameter selection method for kernel functions in SVM. The proposed method tries to estimate the class separability by cosine similarity in the k...
| Asıl Yazarlar: | , |
|---|---|
| Materyal Türü: | Makale |
| Dil: | English |
| Baskı/Yayın Bilgisi: |
SAGE Publishing
2014-06-01
|
| Seri Bilgileri: | Journal of Algorithms & Computational Technology |
| Online Erişim: | https://doi.org/10.1260/1748-3018.8.2.163 |