How does adding regularization help in avoiding overfitting?
- By adding noise to the training data
- By fitting the model closely to the training data
- By increasing model complexity
- By reducing model complexity
Regularization helps in avoiding overfitting by "reducing model complexity." It adds a penalty to the loss function, constraining the weights and preventing the model from fitting too closely to the training data.
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