Regularization

Regularization is any technique that discourages a model from becoming overly complex, such as penalizing large weights or randomly disabling units, in order to reduce overfitting and improve generalization.

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

Also called L1 regularization, L2 regularization, Weight decay.