title: Is it possible to train an SVM or Random Forest on the final layer feature of a Convolutional Neural Network using Keras?
body: <p>I have designed a Convolutional Neural Network in Keras for image classification with several convolution/max-pooling layers, one densely connected hidden layer and softmax activation on the final layer. I want to replace softmax with an SVM or Random Forest in the final layer to see if that yields a better accuracy. Is there any way to do it in Keras?</p>