Patient-based analysis was carried out using LOOCV.

Table 1 shows the obtained performance measures of nine employed classification algorithms for differentiation between RBP chains and Ctrl chains, in a LOOCV analysis.

The unbiased methylation age acquired using LOOCV in the WHZH panel showed a similar prediction accuracy with a correlation coefficient of 0.95 and a RMSE of 4.05 (Figure 1).

The parameters of LS-SVM models ([gamma] and [sigma]) were optimized by minimizing the prediction errors of leave-one-out cross validation (LOOCV) using the Simplex optimization.

For CMFMDA, we can obtain its test results with three different ways: 5-fold CV, Local LOOCV, and global LOOCV.

In the following experiments, a leave-one-out-cross-validation (LOOCV) strategy is conducted to evaluate every HAR method.

Additionally, the leave-one-out cross- validation (LOOCV) method was used to evaluate the accuracy of these parameters in determining mentor's satisfaction.

In this study, Leave-one-out cross-validation (LOOCV) was used, and the discrimination percentage was calculated based on the number of cases that were correctly predicted by the discriminant function.