📕 subnode [[@KGBicheno/l2_regularization]]
in 📚 node [[l2_regularization]]
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garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/L2_Regularization.md by @KGBicheno
L2 regularization
Go back to the [[AI Glossary]]
A type of regularization that penalizes weights in proportion to the sum of the squares of the weights. L2 regularization helps drive outlier weights (those with high positive or low negative values) closer to 0 but not quite to 0. (Contrast with L1 regularization.) L2 regularization always improves generalization in linear models.
📖 stoas
- public document at doc.anagora.org/l2_regularization
- video call at meet.jit.si/l2_regularization