Which of the following statements accurately describes the purpose of regularization in machine learning? Select all that apply.

Group of answer choices

Regularization involves splitting the dataset into multiple subsets to train the model iteratively.

Regularization penalizes large coefficients in the model to prevent overfitting.

Regularization is applied to ensure that the model performs equally well on both training and test data.

Regularization can prevent the model from learning noise in the training data.