semi-supervised learning
Semi-supervised learning is a machine learning approach that combines both labeled and unlabeled data during training to make predictions or classify new instances. It leverages the limited labeled data available along with the abundance of unlabeled data to improve accuracy and generalization of the model.
Requires login.
Related Concepts (16)
- active learning
- clustering-based approaches
- co-training
- deep learning
- ensemble methods
- generative models
- graph-based methods
- label propagation
- manifold learning
- multi-instance learning
- proxy-label learning
- self-training
- transfer learning
- unlabeled data
- unsupervised feature learning
- weakly supervised learning
Similar Concepts
- adversarial machine learning
- association rule learning
- collaborative learning
- machine learning
- machine learning algorithm
- machine learning algorithms
- machine learning and deep learning
- machine learning for decision-making
- machine learning with human computation
- quantum supervised learning
- quantum unsupervised learning
- simulation-based learning
- supervised learning
- supervision
- unsupervised learning