Regularisation

Anything that deliberately makes fitting the training data harder, in exchange for better performance on data the model has not seen. Weight decay, dropout, early stopping and data augmentation are all forms of it.

A definition is not an understanding. This is taught properly in Regularisation and validation, hands on, part of Overfitting & regularisation.

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Terms from the same topic

Overfitting Underfitting Dropout Early stopping Held-out set Train/validation/test split Cross-validation Data leakage