I am using Matlab R2018b and am trying to infuse SVM classifier within CNN. My plan is to use CNN only as a feature extractor and use SVM as the classifier. I know people have already implemented it a few years back either in tensorflow or in other platforms. In implementing this I got stuck at a point during backward propagation. I got puzzled about which loss function I need to implement to upgrade the gradients and the parameters.
Few points came up during this:
1. I got a feeling to implement the hinge loss here. But which form of hinge loss should I implement? Should I move on to the second form of hinge loss implementation for calculating loss during backward propagation?
2. Besides, calculating the backward loss, should I calculate the forward loss as well to find out the loss occurred in the model?
Any form of advice doing this CNN-svm infusion will be appreciated as I am unable to find any such material implemented in Matlab to get help.
Thanks.