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from sklearn.ensemble import RandomForestRegressor

from sklearn.ensemble import RandomForestRegressor
reg = RandomForestRegressor(n_estimators=200, random_state=101)
reg.fit(X_train, y_train)
accuracy = reg.score(X_test, y_test)
accuracy = accuracy * 100
accuracy = float('{0:.4f}'.format(accuracy))

preds = reg.predict(X_test)
print('The prediction is:', preds[1], 'But the real value is:', y_test[1])