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from sklearn.ensemble import RandomForestRegressor

from sklearn.metrics import mean_squared_error

model = RandomForestRegressor(random_state=1)

model.fit(X_train, y_train)
preds_valid = model.predict(X_valid)

print(mean_squared_error(y_valid, preds_valid, squared=False))