Table 3.
Relevant approaches according to the amount of labeled and unlabeled data available
| Amount of available data | Some unlabeled data | No unlabeled data |
|---|---|---|
| Enough labeled data to train a supervised model | Supervised learning | Supervised learning |
| Data augmentation | Data augmentation | |
| Semi-supervised learning | ||
| Active learning | ||
| Some labeled data, but not enough to train a supervised model | Data augmentation | Data augmentation |
| Semi-supervised learning | Transfer learninga | |
| Active learning | ||
| Transfer learninga | ||
| Self-supervised learninga | ||
| Few/one/zero-shot learninga | ||
| No labeled data | Active learning Zero-shot learninga |
Zero-shot learninga |
a
Large labeled datasets are required for pre-training.