 / threshold for all splits on a given level aka symmetric trees
- Symmetric trees are "different" but can be much faster
- supports missing value
- GPU training
- monotonicity constraints
- uses bagged and smoothed version of target encoding for categorical variables
- lots of tooling
]
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# Gradient Boosting Advantages

- Very fast using HistGradientBoosting (or XGBoost, LightGBM)
- Small model size
- Typically more accurate than Random Forests

- "old" GradientBoosting in sklearn is compa