The selection of the kernel function parameter and error penalty factor affected the precision of the support vector machine (SVM) significantly.
核函数参数和误差惩罚因子的选择对支持向量机模型（SVM）的精度有较大影响。
In the paper, GBGM-GA is seen the optimization technique combining KPCA and GA, and is suitable to the optimization selection of kernel function parameter.
本文采用高斯变异遗传算法作优化技术，实现了KPCA和GA的集成，适合核函数参数的优化选择。
In the paper, GBGM-GA is seen the optimization technique combining KPCA and GA, and is suitable to the optimization selection of kernel function parameter.
本文采用高斯变异遗传算法作优化技术，实现了KPCA和GA的集成，适合核函数参数的优化选择。
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