in which situation different methods in multi-labe

问题:

I have read this to learn about various method in multi-label classifiers. I learned that there are 3 techniques to do multi-label classifications:

1.Problem Transformation
2.Adapted Algorithm
3.Ensemble approaches

In the category of Problem transformations there are more three sub categories:

a.Binary Relevance
b.Classifier Chains
c.Label Powerset

I know that when we want better result we should apply the ensemble model. I would like to know in which situations the other different algorithm we should use.

I know how they differently work, but I do not know when I should use each of them.

And Also there is only two method implemented for Adapted Algorithm. what if I want other methods but implemented in adapted algorithm approach?

Please let me know if my statements are not clear.

Thanks,