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Tree-Based Models
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Decision trees
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165.
Decision Tree Depth and Overfitting
easy
What is the primary hyperparameter used to control overfitting in a decision tree?
A
The minimum impurity decrease, which controls whether splits are accepted based on a fixed threshold
B
The number of features considered at each node, which controls the diversity of splits
C
The maximum depth of the tree, which limits how many splits can be made from root to leaf
D
The learning rate, which controls how quickly the tree adapts to new training examples during fitting
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