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The performance was evaluated using a nested leave-one-out cross-validation with a parameter optimization using 10-fold cross-validation repeated 2 times.
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To get an unbiased estimate, we conducted a nested leave-one-out cross validation in NetCBI.
BACCs were computed using nested leave-one-out cross-validation and were regarded as significant if p < 0.01.
The classification performance was measured using nested leave-one-out cross-validation, where feature selection and hyperparameter selection were performed in the inner cross-validation loop independently of the test sample of the outer cross-validation loop (Additional file 3).
An analogue setup was used to compute nested leave-one-out cross-validation results to compare the predictive performance of the support vector machine in combination with the jCompoundMapper encodings to literature results.
So it is possible to execute only single leave-one-out cross-validation and single nested leave-one-out cross-validation.
Table 4 and 5 summarize the results of the nested leave-one out cross-validation according to the mean squared error and Pearson's correlation coefficient.
We used the C-SVM formulation, which uses a two-level nested cross-validation to optimize the misclassification penalty parameter C using a leave-one-out procedure within the main leave-one-out loop [50].
Models were cross-validated on independent data points using a leave-one-out jackknife method.
The performance of the classifier was tested using a leave-one-out cross-validation strategy.
Experiment was carried out using a "leave-one-out" cross-validation scheme.
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