Beginner
Artificial Intelligence & Machine Learning
Q24 / 100
What is the purpose of regularization in ML?
Correct! Well done.
Incorrect.
The correct answer is B) Adding a penalty term to the loss function to constrain model complexity and prevent overfitting
B
Correct Answer
Adding a penalty term to the loss function to constrain model complexity and prevent overfitting
Explanation
L1 regularization (Lasso): adds λ|w| — promotes sparsity (many weights = 0). L2 regularization (Ridge): adds λw² — shrinks weights toward 0. Elastic Net combines both. Dropout is regularization for neural networks.
Progress
24/100