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R-squared and MNSE error computation

# Import mean_squared_error
from sklearn.metrics import mean_squared_error

# Compute R-squared
r_squared = reg.score(X_test, y_test)

# Compute RMSE
rmse = mean_squared_error(y_test, y_pred, squared=False)

# Print the metrics
print("R^2: {}".format(r_squared))
print("RMSE: {}".format(rmse))

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R-squared and MNSE error computation

# Import mean_squared_error
from sklearn.metrics import mean_squared_error

# Compute R-squared
r_squared = reg.score(X_test, y_test)

# Compute RMSE
rmse = mean_squared_error(y_test, y_pred, squared=False)

# Print the metrics
print("R^2: {}".format(r_squared))
print("RMSE: {}".format(rmse))

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R-squared and MNSE error computation

R-squared and MNSE error computation

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