Can someone explain me what are the various strategies for solving text multilabel classification problems with Deep Learning models?
Is it right to “convert” the problem to multiclass classification problem? What I mean?
If for example I have 3 labels and an instance can belong to one, two or even three labels or a combination of these 3 labels I can convert the problem as a multiclass classification problem of 7 classes:
(A), (B), ©, (AB), (AC), (BC), (ABC).
Is it right? If not how can I handle it?