I have one question about the regression and classification loss. I have trained a network which outputs denoised data and its corresponding events picked in binary(0 or 1). At the moment I am using only MSE loss and then set some threshold criteria for binary data, to convert to 0 or 1.
Is it possible that I have two types of losses(one classification and other regression) added and backpropagated for this type of network? If not, what are the other alternatives?