<jupyter_start><jupyter_text>* RMSE is a measurment to measure the performance of a linear regression model. It's full name is  Root Mean Square Error. The RMSE measured on the same scale with the same units as y. Since it is   the way to measuer the difference between the value we predict and the actual value. Therefore,   a better linear regression model should have the smallest RMSE. * The formula to define the RMSE is: $\large RMSE(\vec{X}, h_\vec{\theta}) = \sqrt{\frac{1}{m} \sum_{i=1}^m (\vec{\theta}^\top\vec{x}^i - y^i)^2}$* In the model above, the RMSE is 77257 which is not good. I should do more data preprocessing in the future.  For example, remove the outliers.<jupyter_code>y.describe()<jupyter_output><empty_output>
StarcoderdataJupyterStructuredCleanDedup