I want to define custom cross entropy loss penalizing different class errors.
Categorical cross entropy loss =
I want to give different weights to different prediction errors. e.g. For a 3-class problem, below cost matrix is defined.
Is it fair to define new cost entropy loss function as below?
Where C_{ij} - Cost of classifying class ‘i’ as class ‘j’