The objective in extreme multi-label classification is to learn feature architectures and classifiers that can automatically tag a data point with the most relevant subset of labels from an extremely large label set. This repository provides resources that can be used for evaluating the performance of extreme multi-label algorithms including datasets, code, and metrics.
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