# How we can understand that model overfitting by using RMSE?

Our median values range : 120K-265K, and avg.error is 157 K (result of RMSE).

How I can interpret that is overfitting, underfitting , or a good model?

I thought if I divide as like that: 157000/120000 and 157000/265000...I can get some inferences from them.

from sklearn.metrics import mean_squared_error as mse
inst_pred = lin_reg.predict(instance_prepared)

inst_mse = mse(instance_label, inst_pred )

inst_rmse = np.sqrt(inst_mse)

print(inst_rmse)


(It is cited from Hands-on ML book.)