To prevent a model from becoming too complex and overfitting the training data, ________ techniques are often applied.

  • Regularization
  • Optimization
  • Stochastic Gradient Descent
  • Batch Normalization
Regularization techniques add penalties to the loss function to discourage complex models, helping prevent overfitting and improving model generalization.
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