Overfitting

Methods to prevent overfitting in Machine Laerning L2 Regularization (Ridge Regression) L2 regularization adds a penalty term to the loss function based on the squared magnitudes of the model’s weights. This penalty discourages large weight values and encourages the model to use smaller weights, leading to a smoother and more generalized solution. The regularization term is controlled by a hyperparameter (lambda or alpha) that balances the trade-off between fitting the training data and keeping the weights small....