A character can be food-themed, embroidered and seasonal at the same time. Forcing those attributes into one exclusive class can discard useful information.
Scikit-learn distinguishes multiclass classification from multilabel tasks in which samples can have multiple labels. Scikit-learn — multiclass.
Define the taxonomy
Separate mutually exclusive categories from independent attributes. State how unknown, absent and unreviewed tags are represented. A clear label structure makes both annotation and evaluation easier to interpret.
Evaluate the intended output
For an archive tool, inspect which combinations are missed or incorrectly added. Do not report a single category score as though it describes every independent tag. The output format should match how the product team actually uses the information.
Source reviewed 25 October 2026. Interpretation and original diagrams: PLUSHIP / Qunhe. Examples are illustrative.
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