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Tree-Based Models
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Random Forest
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297.
Feature Subsampling in Random Forest
easy
What is the purpose of feature subsampling at each split in a Random Forest?
A
To speed up training by reducing the number of split candidates evaluated at each node
B
To prevent high-cardinality features from dominating the splits across all trees in the ensemble
C
To decorrelate the trees so that averaging them provides greater variance reduction
D
To ensure each feature is used the same number of times across the full ensemble of trees
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