Translations:Overfitting and Regularization/14/en: Difference between revisions

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    The gradient of the regularization term is <math>\lambda \theta</math>, so each weight is multiplicatively shrunk toward zero at every update — hence the name '''weight decay'''. The hyperparameter <math>\lambda</math> controls the regularization strength.
    The gradient of the regularization term is <math>\lambda \theta</math>, so each weight is multiplicatively shrunk toward zero at every update — hence the name '''{{Term|weight decay}}'''. The {{Term|hyperparameter}} <math>\lambda</math> controls the regularization strength.

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    Message definition (Overfitting and Regularization)
    The gradient of the regularization term is <math>\lambda \theta</math>, so each weight is multiplicatively shrunk toward zero at every update — hence the name '''{{Term|weight decay}}'''. The {{Term|hyperparameter}} <math>\lambda</math> controls the regularization strength.

    The gradient of the regularization term is $ \lambda \theta $, so each weight is multiplicatively shrunk toward zero at every update — hence the name weight decay. The hyperparameter $ \lambda $ controls the regularization strength.

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