I understand that train / test split is important for these types of problems - ensuring label combinations are represented well in both (scikit-multilearn implements their own split method for this purpose).
My current goal is to understand how this works so that I can evaluate it properly - I am reading from here primarily.
I am a little confused by the output of the
get_combination_wise_output_matrix method. I understand at a high level it is giving me a breakdown of counts of label combinations for whatever order I specify.
The first question I have is does
(5, 5): 1, mean anything other than the label at index 5 appears once, and this number is repeated for... reasons?
Additionally I haven't yet found any literature evaluating how / when to use different orders (my current approach to this is to qualitatively evaluate a few different options that seem reasonable given the specific problem I am trying (desperately) to solve
Thanks in advance for any help!