medical-13
Multi-Label Classification
3260 papers • 126 benchmarks • 313 datasets
Multi-Label Classification is the supervised learning problem where an instance may be associated with multiple labels. This is an extension of single-label classification (i.e., multi-class, or binary) where each instance is only associated with a single class label. Source: Deep Learning for Multi-label Classification
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Benchmarks
These leaderboards are used to track progress in multi-label-classification-53
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Dataset
Best Model
Actions
MS-COCO
MS-COCO
PASCAL VOC 2007
PASCAL VOC 2007
CheXpert
CheXpert
Libraries
iUse these libraries to find multi-label-classification-53 models and implementations
3 papers 487
