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Supervised Learning
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Tree-Based Models
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Gradient Boosting (XGBoost, LightGBM)
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327.
Gradient Boosting Construction
easy
How does gradient boosting build its ensemble of trees?
A
Sequentially, where each new tree fits the residual errors of the current ensemble
B
Iteratively, where each tree is pruned to remove the weakest splits from the previous tree
C
In parallel, where each tree is trained on a different bootstrap sample of the training data
D
Randomly, where each tree is assigned a random weight and combined into a weighted average
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