I want to implement a network which can predict ‘between-class’ label.
I mean, when feed the model with the data created by the data from class A and the data from class B, the label of the created data should not be [1 , 1], but [0.5, 0.5].
It is a bit like ‘multi-label’, but it ’s actually different. Because it is no longer possible to use one-hot label.
What confuses me is how to define and use the loss function?