دورية أكاديمية
Improved Classification Performance of Support Vector Machine Technique Using the Genetic Algorithm
| العنوان: | Improved Classification Performance of Support Vector Machine Technique Using the Genetic Algorithm |
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| المؤلفون: | Omar Qasim, Mustafa Abed Alhafedh |
| المصدر: | Al-Rafidain Journal of Computer Sciences and Mathematics, Vol 12, Iss 2, Pp 49-60 (2018) |
| بيانات النشر: | Mosul University, 2018. |
| سنة النشر: | 2018 |
| المجموعة: | LCC:Mathematics LCC:Electronic computers. Computer science |
| مصطلحات موضوعية: | genetic algorithm, support vector machine, parameter selection, Mathematics, QA1-939, Electronic computers. Computer science, QA75.5-76.95 |
| الوصف: | In this research, the genetic algorithm was proposed as a method to find the parameters of support vector machine, specifically the σ and c parameters for kernel and the hyperplane respectively. Based on the Least squares method, the fitness function was built in the genetic algorithm to find the optimal values of the parameters in the proposed method. The proposed method showed better and more efficient results than the classical method of support vector machine which adopts the default or random values of parameters σ and c in the classification of leukemia data. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | Arabic English |
| تدمد: | 1815-4816 2311-7990 |
| Relation: | https://csmj.mosuljournals.com/article_163581_76178d0f91ac6b09b3097e3517e23b80.pdf; https://doaj.org/toc/1815-4816; https://doaj.org/toc/2311-7990 |
| DOI: | 10.33899/csmj.2018.163581 |
| URL الوصول: | https://doaj.org/article/4807684acfdd40eebe9c7f7e70514ab9 |
| رقم الأكسشن: | edsdoj.4807684acfdd40eebe9c7f7e70514ab9 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 18154816 23117990 |
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| DOI: | 10.33899/csmj.2018.163581 |