Answer: All the above.

## Explanation Regularization techniques are used to prevent overfitting in machine learning models by adding a penalty term to the loss function. The three main types mentioned are: - **A. Ridge regression (L2 regularization)**: Adds a penalty equal to the square of the magnitude of coefficients - **B. LASSO (L1 regularization)**: Adds a penalty equal to the absolute value of the magnitude of coefficients - **C. A hybrid of Ridge and LASSO (Elastic Net)**: Combines both L1 and L2 penalties Since all three options (A, B, and C) are valid regularization techniques, the correct answer is **D. All the above**.

Author: LeetQuiz Editorial Team