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Which hyperparameter most directly controls overfitting in gradient boosting?

A Learning rate combined with the number of trees and maximum depth
B The random seed
C The number of features in the dataset
D The batch size

Answer

Learning rate combined with the number of trees and maximum depth

A lower learning rate with more trees usually generalises better. Early stopping on a validation set is the practical safeguard.

All Machine Learning MCQs

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