How does Random Forest behave under extreme class imbalance with rare event detection?

RF tends to bias toward majority class unless explicitly reweighted or resampled.

In extreme imbalance, impurity reduction favors majority class splits, leading to poor minority recall. Techniques like class weighting, balanced subsampling, and threshold tuning are required to make RF sensitive to rare events.