Fig. 2

3 × 3 nested cross-validation (CV) method. 24,145 drug pairs tested on five cell lines from the DrugComb database were divided into three folds in the outer loop of the nested CV, where one fold was used as a test dataset while the other two folds were further divided into three folds in the inner loop. In each round of the inner loop, two folds were used as a training dataset, and the other fold was used as a validation set in a grid search for the best hyperparameter set. The best hyperparameter set (identified based on the average Pearson correlation coefficients obtained across each round of the three inner loops) was used to train a model, and the model was evaluated using the test set from the outer loop