text_plain_output_1.png
n_samples = 1000
n_features = 10
n_classes = 2
n_estimators = 25
max_depth = 10
model = cuRF(max_depth=max_depth, n_estimators=n_estimators, random_state=0)
trained_RF = model.fit(X_train, y_train)

predictions = model.predict(X_test)