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The technique that reduces model complexity to prevent overfitting is called ________.

  1. Corporation for Assigned Names and Numbers / ICANN
  2. Common
  3. Pruning
  4. Regularization

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.

Topic Data Science
Exam Relevance Banking, SSC JE, UPSC
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