Consider a scenario where you need to combine supervised and unsupervised techniques. What might be a use case for semi-supervised learning?
- Classification with abundant labeled data
- Classification with limited labeled data
- Clustering without labels
- Real-time decision-making
Semi-Supervised Learning is particularly useful for classification tasks when there are limited labeled data, combining strengths of supervised and unsupervised techniques.
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