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L1 regularization adds the sum of the absolute values of parameters as a penalty term in the loss function, and its geometric properties cause the optimal solution to tend toward the coordinate axes; L2 regularization adds the sum of squared parameters, penalizing large coefficients without driving them to zero.
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10/10/2026
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