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Compare feature importances created between cuml and sklearn RandomForestClassifiers

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Introduce

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.

Requirements

python == 3.10

rapids == 23.06

scikit-learn == 1.3.0

matplotlib == 3.7.2 (optional)

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Compare feature importances created between cuml and sklearn RandomForestClassifiers

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