L2 Regularization Hyperparameter in trainingOptions

Andrea-bonfante asked: 2021-06-15 deep neural nets , l2 regularization , trainingoptions , hyperparameters

Explore L2 regularization hyperparameter tuning in MATLABs trainingOptions. Learn how to optimize your models, prevent overfitting, and improve accuracy. Get s

Expert Answer

John Williams answered . 2025-07-30 13:57:28

The most common values of the regularization parameter are often on a logarithmic scale between 0 and 0.1, such as 0.1, 0.001, 0.00001 etc.

Setting the regularization parameter to zero may cause the network to overfit to the training data and reduces the generalizing capability of the network. Changing the regularization parameter as such doesn’t affect other carefully tuned parameters within the model. But it’s effects may be observed during the convergence of the loss function.

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