What is 'Regularization'?

What is 'Regularization'?

Approach: Define adding a penalty to the loss function to prevent overfitting.

The process of adding information or a penalty term to a model to prevent overfitting. It penalizes complex models, encouraging them to be simpler and generalize better.

Follow-up: Give an example of regularization in Neural Networks (e.g., Dropout).

Key concepts: overfitting, l1, l2, complexity penalty.