Usually, the steepest descent algorithm is used to find the minimum of LOO upper-bound. However, it often gets local optimal solution.
由于该方法易陷入局部最优解，提出了一种基于混合遗传算法求解LOO上界极小点的核参数选择方法。
It is of lower complexity in computation and far more easy to be implemented as compared with the original steepest descent algorithm.
新算法与传统的最陡下降算法相比，具有运算量小、容易实现等优点。
It is of lower complexity in computation and far more easy to be implemented as compared with the original steepest descent algorithm.
新算法与传统的最陡下降算法相比，具有运算量小、容易实现等优点。
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