The conversation between human and AI assistant.
How do random forests and boosted decision trees compare?
Thanks for explaining that. Do you have any examples of when to use one over the other?
Sure! Random forests are often used for large datasets, where they can handle a mix of categorical and numerical data, and in settings where interpretability is important. Boosted decision trees are often used when high accuracy is important and the dataset is smaller. They can also be used in applications where interpretability is not as crucial.