There's something strange about the ROC curve here. It seems that the feature engineered and logistic regression methods can pick out some examples very easily

There's something strange about the ROC curve here. It seems that the feature engineered and logistic regression methods can pick out some examples very easily (20% true positive rate at a very low false positive rate) but the CNN seems to not be able to make many predictions at a low false positive rate. It then catches up later. It's almost like it can't pick out the easy examples, but does just as good a job on the harder ones.