ually, this is more accurate than
random forests.

The question is for the same number of estimators, how does
low versus high learning rate changes?

High learning rate allows you to fit the data more strongly
and also overfit the data more strongly.

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# When to use tree-based models
- Model non-linear relationships
- Doesn’t care about scaling, no need for feature engineering
- Single tree: very interpretable (if small)
- Random forests very robust, good benchmark
- Gradient boosting o