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Supervised Learning
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Tree-Based Models
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Random Forest
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664.
Rationale for Ensemble Averaging
easy
Why does Random Forest aggregate predictions from many trees rather than using a single deep tree?
A
Averaging reduces bias while preserving the low variance of individual deep trees
B
Averaging reduces variance while preserving the low bias of individual deep trees
C
Averaging eliminates irreducible error by combining complementary predictions from each tree
D
Averaging improves calibration by converting raw class counts into smooth probability estimates
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