Hi Ninoslav!



 Legolas:

Isn’t it true when I consider both ‘components’, I should push the model to train for predicting ‘both components’, in other words, a four-class model – this way through ‘components’?


Yes,  you can look at it this way, and you can do it this way.
The details of training will be different, but there is an equivalence
between a multi-label, two-class problem and a single-label,
four-class problem.
Let’s say that in the first instance your classes are A and B, and in
the second, 0, 1, 2, 3.
Then:
   A--no, B--no  -->  0
   A-yes, B--no  -->  1
   A--no, B-yes  -->  2
   A-yes, B-yes  -->  3

gives an explicit mapping between the two problems.
My intuition tells be you will get better training and better results treating
this as a multi-label, two-class problem.  But you should also be able to
get things to work treating this as a single-label, four-class problem.
Your call.
Best.
K. Frank