The optimal parameters of mathematics model were studied using leave-one-out cross validation method.
利用内部交叉验证和自动优化功能对预测模型进行了优化，确定了最优建模参数。
In this paper, soft sensor modeling method based on Least Square SVM (LS SVM) is proposed, and cross validation method is used to select hyper-parameter of LS SVM model.
本文研究了基于最小二乘支持向量机的软测量建模方法，并用交叉验证的方法进行支持向量机参数选择。
In the first block, a modified generalized Cross validation blur identification method was proposed.
在第一部分，提出了一种改进的广义交叉验证模糊辨识方法。
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