e/Multi-label classification

Information
has gloss	eng: Multi-label classification is a concept in mathematics and machine learning. Traditional single-label classification is concerned with learning from a set of examples that are associated with a single label l from a set of disjoint labels L, \|L\| > 1 . In multi-label classification, the examples are associated with a set of labels Y \subseteq L. In the past, multi-label classification was mainly motivated by the tasks of text categorization and medical diagnosis. Nowadays, we notice that multi-label classification methods are increasingly required by modern applications, such as protein function classification, music categorization and semantic scene classification.
lexicalization	eng: Multi-Label Classification
instance of	c/Classification algorithms