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On the Stratification of Multi-label Data
[chapter]
2011
Lecture Notes in Computer Science
Stratified sampling is a sampling method that takes into account the existence of disjoint groups within a population and produces samples where the proportion of these groups is maintained. In single-label classification tasks, groups are differentiated based on the value of the target variable. In multi-label learning tasks, however, where there are multiple target variables, it is not clear how stratified sampling could/should be performed. This paper investigates stratification in the
doi:10.1007/978-3-642-23808-6_10
fatcat:67rmrxaau5gx7mpiuudj7wadee