Question: What is the purpose of regularization in machine learning?Answer: Regularization is used to prevent overfitting in machine learning models by adding a penalty term to the cost function. It discourages the model from fitting the training data too closely and encourages generalization to new, unseen data. |
Save For Revision
Bookmark this item, mark it difficult, or place it in a revision set.
Log in to save bookmarks, difficult questions, and revision sets.
Is it helpful? Yes No
Most helpful rated by users:
- Explain the concept of feature engineering.
- What is the purpose of regularization in machine learning?
- Explain the term \'hyperparameter\' in the context of machine learning.
- What is the purpose of the activation function in a neural network?
- Explain the term \'precision\' in the context of classification.