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On the other hand, in Approach 2, feature selection is performed using the training set within each cross-validation fold, and so the resulting cross-validation error rate is valid.
To avoid overfitting of the model, which would generate an overoptimistic result, cross-validation, by repeated holding-out of 10% of the patients, was incorporated in the analysis.
As the result, cross-validation experiments show that the proposed method achieves both high coverage and high prediction accuracy at a practical level, and consistently outperforms the previous method.
To ensure robust results, cross validation was done using multiple (20) iterations of random subset withholding (leave 10% out).
The results of cross-validation show the smoothing effect of the spatial prediction map using RMSE value.
Thus, the results of cross-validation provided further evidence for the construct validity of the HBS with 25 items.
Results from cross-validation experiments suggest that a majority of the models will perform similarly to calibration runs.
To assess the quality of estimation, the ME and the MPE were calculated from the results of cross-validation.
We also examine our choice of hyperparameters by describing results of cross-validation experiments done on a custom dataset.
Stage 5: Find the two pairs of parameter values that give the best and second-best results by cross-validation technique.
The results of cross-validation are the sum of the squared prediction errors, sometimes called the predicted residual sum of squares (PRESS).
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