3260 papers • 126 benchmarks • 313 datasets
Extreme Multi-Label Classification is a supervised learning problem where an instance may be associated with multiple labels. The two main problems are the unbalanced labels in the dataset and the amount of different labels.
(Image credit: Papersgraph)
These leaderboards are used to track progress in extreme-multi-label-classification-90
No benchmarks available.
Use these libraries to find extreme-multi-label-classification-90 models and implementations
No datasets available.
No subtasks available.
Adding a benchmark result helps the community track progress.