Machine Learning
Regularization
Machine Learning· Intermediate
Definition
A set of techniques that reduce overfitting by adding a penalty to the loss function for model complexity. L1 regularization (Lasso) drives weights to zero, producing sparse models; L2 (Ridge) shrinks weights toward zero. Dropout is a regularization technique specific to neural networks.
Tags
#overfitting#L1#L2#dropout#generalization
MS
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