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from sklearn.ensemble import RandomForestRegressor

from sklearn.metrics import mean_squared_error

from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import mean_squared_error
model = RandomForestRegressor()
model.fit(X_train, y_train)
pred = model.predict(X_valid)
mse = mean_squared_error(y_valid, pred, squared=False)
print(mse)