However, the good match between the ML-attribution and FPA vectors for 1 does not mean that the ML model has learned the contribution of each FP fragment correctly. Out of the 41 different ECFP4 fragments that describe 1 only nine (Figure ) make a significant (>0.05) contribution to the logP value and a FP with only these nine bits reproduces the predicted logP value to within 0.25 units. All but one of these fragments (fragment 90) are ECFP2 fragments and none of these fragments derive from the pyrrolidone ring. So according to the ML model the net logP contribution of the pyrrolidone ring is nearly zero because all associated fragments each make nearly zero contributions, in contrast to the FPA vector where most fragments make sizeable positive or negative contributions that mostly cancel. The predicted logP value is slightly positive (0.26) while the ground truth is negative (-1.12) and the error (1.38) is more than twice the model MAE (0.58) (Table ). Comparison of the ML-attribution vector to the ground truth and FPA vectors clearly show that the discrepancy arises from the region of the molecule involving the N cation. Indeed, the error is eliminated by removing the proton, which also increases the overlap to 0.75 (Figure ).