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Ridge Regression
Ridge Regression
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What is the key difference between L1 (Lasso) and L2 (Ridge) regularization?
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A.
L1 applies a penalty only to the single largest weight in the model, while L2 distributes the penalty uniformly across all weight parameters
B.
L2 produces sparse solutions with exact zero weights, while L1 only shrinks weights toward zero without reaching exactly zero
C.
L1 regularization uniformly dominates L2 for all regression and classification problems regardless of the underlying sparsity structure
D.
L1 penalizes the sum of absolute values of weights and produces sparse solutions; L2 penalizes the sum of squared weights and shrinks all weights toward zero
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