李刚, 赵香. 基于遗传算法的最小平方支持向量机[J]. 信阳师范学院学报(自然科学版), 2009, 22(1): 134-136.
引用本文: 李刚, 赵香. 基于遗传算法的最小平方支持向量机[J]. 信阳师范学院学报(自然科学版), 2009, 22(1): 134-136.
LI Gang, ZHAO Xiang. The Least Square Support Vector Machine(LS-SVM) Based on Genetic Algorithm[J]. Journal of Xinyang Normal University (Natural Science Edition), 2009, 22(1): 134-136.
Citation: LI Gang, ZHAO Xiang. The Least Square Support Vector Machine(LS-SVM) Based on Genetic Algorithm[J]. Journal of Xinyang Normal University (Natural Science Edition), 2009, 22(1): 134-136.

基于遗传算法的最小平方支持向量机

The Least Square Support Vector Machine(LS-SVM) Based on Genetic Algorithm

  • 摘要: 支持向量机和最小平方支持向量机的分类中,采用人工方法选取特征子集和参数,需要付出较高的时间代价.为此,本文提出基于遗传算法的最小平方支持向量机,借助于遗传算法的全局随机搜索能力,自动确定特征子集、参数,为特征子集、参数的优化选择提供了一条有效途径.

     

    Abstract: Feature subset and parameters are often selected manually in classification problem based on support vector machine(SVM) and least square support vector machine(LS-SVM),which is very time consuming.In this paper,an automatic method for selecting the parameter subset and parameters of LS-SVM based on genetic algorithms is presented.The selection of feature subset and parameters is automatic by means of the whole seeking ability of genetic algorithm,which provides an effectual approach to the selection of fea...

     

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