Study
Machine Learning · Random forest
Bagging many decorrelated trees: bootstrap samples, random feature subsets, out-of-bag score, and feature importances.
- A random forest averages many deep trees trained on bootstrap samples with random feature subsets, which cuts variance.
- The out-of-bag score is a free validation estimate from the rows each tree never saw.