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基于PSO的LS-SVM特征选择与参数优化算法

于 2020-12-03 发布
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代码说明:

首先产生若干种群(特征子集),然后用PSO 算法对特征及参数进行优化。在UCI 标准数据集上进行的仿真实验表明,该算法可有效地找出合适的特征子集及LS-SVM 参数,且与基于遗传算法的最小二乘支持向量机算法(GALS-SVM)和传统的LS-SVM 算法相比具有较好的分类效果。

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