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| 基于育种算法的SVM参数优化 | |
| 引用本文： | 王东霞,张楠,路晓丽.基于育种算法的SVM参数优化[J].安徽大学学报(自然科学版),2009,33(4). |
| 作者姓名： | 王东霞 张楠 路晓丽 |
| 作者单位： | 1. 济源职业技术学院,计算机系,河南,济源,454650 2. 西北大学,数学系,陕西,西安,710127 3. 西北大学,公共管理学院,陕西,西安,710127 |
| 基金项目： | 河南省科技攻关基金资助项目(072102310088);;河南省自然科学基金资助项目(2008A520018) |
| 摘 要： | 支持向量机(SVM)的学习性能主要取决于参数选择.论文基于育种算法提出了混合算法的支持向量机参数优化模型,即将种子或者粒子所对应的适应度取作交叉验证方法中的测试样本集数据的识别率,构成基于混合算法的支持向量机,并通过数值试验验证了该方法的可行性。 |
| 关 键 词： | SVM 参数优化 育种算法 |
Parameters selection of SVM based on breeding algorithm |
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| WANG Dong-xia,ZHANG Nan,LU Xiao-li.Parameters selection of SVM based on breeding algorithm[J].Journal of Anhui University(Natural Sciences),2009,33(4). | |
| Authors: | WANG Dong-xia ZHANG Nan LU Xiao-li |
| Institution: | 1.Department of Computer Science;Jiyuan Vocational and Technical College;Jiyuan 454650;China;2.Department of Mathematics;Northwest University;Xi'an 710127;3.School of Public Management;China |
| Abstract: | The learning performance of Support Vector Machines(SVM) was due to parameters selection.Based on a hybrid algorithm,the article proposed breeding of support vector machine parameters optimization model,the seeds or particle corresponded fitly as a cross validation method of test sample collection of data,constituted the recognition of the hybrid algorithm based on support vector machine,and the numerical experiments showed that this method was feasible. |
| Keywords: | SVM parameters selection breeding algorithm |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |