is this problem a multiclass case? I'm trying to classify my textile design patterns
(let's just think of it as medieval painting)
what I understand of &quot;multilabel classification&quot; is like this:
it outputs multiple possible result out of all those classes (let's say classes are of some artists, style and technique)
so one example could be

possible classes: leonardo, artist1, artist2, baroque, renaissance, whatever, oil, dessin, watercolor
prediction of img1: leonardo da vinci, artist1, renaissance, oilpainting, wtaercolor


but what I want to do is more like:
 - possible classes:




artist
style
technique




leonardo
baroque
oil


artist1
renaissance
dessin


artist2
whatever
watercolor





prediction: {artist: ['leonardo', 'artist1'], (maybe they drew it together)
style: ['renaissance'], 
technique: ['oil', 'watercolor']}

classes are more strictly categorized and but also there could be multiple results from one category of class.
I'm not even sure what should it be called and having hard time to find articels for it.
Can someone please suggest?
It is not a multiclass problem.
It is a multilabel problem. Since, you have the clusters of classes you want to get. You just let the network predict multiple classes and segregate them afterwards. In this case, you will have single classification head.
Other way to do it, is to separately derive multiple classes of article, technique and style. In this case, you will have three classification heads.