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...
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| Главные авторы: | , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
SAGE Publishing
2014-06-01
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| Серии: | Journal of Algorithms & Computational Technology |
| Online-ссылка: | https://doi.org/10.1260/1748-3018.8.2.163 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
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