Regularization for Simplicity: L₂ Regularization | Machine …
https://developers.google.com/machine-learning/crash-course/regularization-for-simplicity/l2-regularization
WebJul 18, 2022 · L 2 regularization term = | | w | | 2 2 = w 1 2 + w 2 2 +... + w n 2. In this formula, weights close to zero have little effect on model complexity, while outlier weights can have a huge impact. For example, a linear model with the following weights: { w 1 = 0.2, w 2 = 0.5, w 3 = 5, w 4 = 1, w 5 = 0.25, w 6 = 0.75 }
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