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。
The classification error rate for normal and early stage DR samples reached 21.35% using a linear classifier and the leave-one-out method.
使用线性分类器进行分类,并用“留一法”统计结果,正常人和早期DR病例的分类错误率为21.35%。
We give the concept of the leave-one-out cross-validation score. We also discuss the best method to choose the bandwidth and give the best value of it.
给出了缺一交叉验证得分的概念,讨论了最优带宽的理论的和实际的选择方法,并得出实际最优带宽的值。
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