One of the things that we discussed in the Formulating the loss function section, was the fact that the class labels are not independent categorical classes, but do have an ordinal sense with the increasing severity of the diabetic retinopathy condition. Hence, it would be worthwhile to perform regression through the defined transfer learning networks, instead of classification, and see how the results turned out. The only thing that we would need to change would be the output unit, from a softmax to a linear unit. We will, in fact, change it to be a ReLU, since we want to avoid negative scores. The following code block shows the InceptionV3 version of the regression network:
def inception_pseudo(dim=224,freeze_layers=30,full_freeze='N'):
model = InceptionV3(weights='imagenet',include_top=False...
