This notebook compare's feature importances which are created between cuml and sklearn RandomForestClassifiers
Feature importances calculated in sklearn needs to use RandomForestClassifier().feature_importances_, while in cuml needs to use this function with one line fixed.
python == 3.10
rapids == 23.06
scikit-learn == 1.3.0
matplotlib == 3.7.2 (optional)