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The technique that reduces model complexity to prevent overfitting is called ________.
Answer: Regularization
Regularization (L1/Lasso, L2/Ridge, Dropout) adds penalty terms to loss function or randomly drops units during training. Prevents overfitting by discouraging complex models. Critical for generalization.