Model Generalization

Model generalization refers to how well a trained model can apply its learned knowledge to new, previously unseen data. A well-generalized model accurately predicts outcomes for new inputs that were not part of the training dataset. Techniques such as cross-validation and using separate validation sets help assess and improve generalization.