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Each of the models was validated with a 10-fold cross-validation test.
The prediction performance of linear regression models was validated using %recovery, relative prediction error and root mean square error for cross-validation.
The accuracy of the numerical models was validated with the relevant experimental outcomes.
The predictive ability of the optimized models was validated by a test set including 18 samples.
The predictability of calibration models was validated with independent data set.
The predictive ability of these models was validated by 28 test set molecules.
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The final models were validated using the PDB validation server.
The O-PLS models were validated by sevenfold cross validation.
The models were validated using the PDB validation server.
The models were validated using 10 × 10 cross-validation.
All models were validated through y-randomization (label scrambling).
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