Which loss function to implement for CNN-SVM infusion
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Hi
I am using Matlab R2018b and am tryinbg to infuse svm classifier within CNN. My plan is to use CNN only as a feature extractor and use SVM as the classifier. Doing this, I got struck in a point during backward propagation. In this phase, I got puzzled as which loss function I need to implement to upgrade the gradients and the parametrers. Few points came up during this:
- I got a feeling to implement the hinge loss here. But which form of hinge loss I will implement?(Should I move on to the second form of hinge loss imeplementation?)
- As in Matlab R2018b, they have updated the parameters after calculating the gradients and forward loss(in their trainer file). If I would like to implement the second form of hinge loss, should i change the usual parameter update code of the Matlab R2018b?
Any form of advice doing this CNN-svm infusion will be appreciated as I am not finding any such material implemented in Matlab to get help.
thanks,
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