Random Forest Classifier From Scratch
Extra-Trees Classifier With Random Thresholds
Reproducible Parallel Forest with Flattened Inference
OOB Error Curve with Warm-Started Forest
Tune Random Forest Hyperparameters by OOB Score
OOB Versus Cross-Validation Gap Experiment
Out-of-Bag Score With Uncovered Samples
Incremental OOB Early Stopping for Forests
Feature Importance Selection
Forest-Level Mean Decrease in Impurity
OOB Permutation Feature Importance
Credit Split Between Correlated Feature Copies
Boruta Feature Selection with Shadow Features
Conditional Permutation Importance for Random Forests
Bootstrap Unique and Out-of-Bag Fractions
Bagging Regressor With Bootstrap Sampling
Balanced Random Forest Bootstrap and Calibration
Random Patches Bagging Meta-Regressor
Proximity Leaf Based Methods
Per-Tree Prediction Spread for Uncertainty
Vectorized Random Forest Proximity Matrix
Quantile Regression Forest Prediction
Proximity-Based RF-Impute for Missing Values
Proximity-Based Outlier Scores