title: Re-train model with new classes
body: <p>I have built an image classifier with 2 classes, say 'A' and 'B'. I have also saved this model, using model.save().</p>
  
  <p>Now, after a certain time, the requirement arose to add one more class 'C'. Is it possible to load_model() and then add only one class to the previously saved model so that we have the final model with 3 classes ('A','B' and 'C'), without having to retrain the whole model, for classes 'A and 'B' again?</p>
  
  <p>Can anyone help?</p>
  
  <p>I have tried this:</p>
  
  <p>I used vgg16 as a base model and pop out its last layer, freeze weights and added one dense layer (DL2), trained it for predicting 2 classes. </p>
  
  <p>Then I added one more dense layer on top of DL2 say DL3, freeze weights and train with class C only but now its always predicting class C.</p>