Semi-supervised learning

Semi-supervised learning is a machine learning approach that combines a small amount of labeled data with a larger amount of unlabeled data to train a model more efficiently.

Semi-supervised learning sits in the Foundations part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.