Question: What is the purpose of the \'bootstrap\' sampling method in Random Forests?

Options:

1. To create a balanced dataset
2. To ensure all features are used
3. To generate multiple subsets of the training data
4. To improve model interpretability

Correct Answer: To generate multiple subsets of the training data

Solution:

Bootstrap sampling allows Random Forests to create multiple subsets of the training data, which helps in building diverse trees.