Regularization

L1 vs. L2 Regularization: A Comparison in Machine Learning In the realm of machine learning, regularization techniques play a crucial role in controlling model complexity and preventing overfitting. Two popular regularization methods are L1 and L2 regularization, each with its distinct characteristics and impact on model weights. L2 Regularization L2 regularization, also known as Ridge regularization, penalizes the sum of squared weights in a model. Mathematically, it adds the square of each weight to the loss function, discouraging large weight values....