Figure 2.

Model performance depending on the architecture and negative data sampling method used for training and benchmarking. The x-axis represents mean AUC for architectures trained and tested on sets generated by the same negative data sampling method. The y-axis represents mean AUC for architectures trained and tested on sets generated by different negative data sampling methods. The architectures on the right of the diagonal perform better when the training and benchmark sample are produced by the same method, while the architectures on the left when the methods are different (A). Box plots with median and interquartile range differences in AUC for architectures (B), training data set sampling method (C) and benchmark data set sampling method (D).