Explain the concept of regularization in Machine Learning. What are some common techniques?

  • Increasing complexity, Gradient Boosting
  • Increasing complexity, L1/L2
  • Reducing complexity, Gradient Descent
  • Reducing complexity, L1/L2
Regularization is a technique to reduce overfitting by adding a penalty term to the loss function. Common techniques include L1 (lasso) and L2 (ridge) regularization, which penalize large coefficients in a model.
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