Dropout

Dropout is a regularization technique that randomly switches off a fraction of neurons during each training step, forcing the network to learn redundant, more robust features and reducing overfitting.

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