Zero-shot learning (ZSL) is a problem setup in machine learning where, at test time, a learner observes samples from classes which were not observed during training, and needs to predict their class. The name is a play on words based on the earlier concept of one-shot learning in computer vision, in which classification can be learned from only one example.
Zero-shot learning (ZSL) is a problem setup in machine learning where, at test time, a learner observes samples from classes which were not observed during training, and needs to predict their class. The name is a play on words based on the earlier concept of one-shot learning in computer vision, in which classification can be learned from only one example.
Source: Wikipedia "Zero-shot learning" · CC BY-SA 4.0
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