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Inclusion of additional constraints (typically a penalty for complexity) in the model fitting process. Used to prevent overfitting / enhance predictive accuracy.

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How does L1 regularization make low-value features more zero than L2?

Below formulas, L1 and L2 regularization Many experts said that L1 regularization makes low-value features zero because of constant value. … However, I think that L2 regularization could also make zero value. Could you please explain the reason why L1 has more tendency to make zero value? …
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