Hi, I’ve got a project where I want to map images to multiple features. The features are both continuous values, binary values and mutli-label values.
I understand that you can combine multiple targets for regression in the last linear layer and than use an appropriate loss function (MSE). However if I combine this for the other features (binary and multi-label) I would need to use sigmoid and softmax? How would you combine such a thing and which loss function would you use?
Or should I train 3 models so I can use the right loss function per model?