Different evaluation metrics for Regression Models



I was just wondering if RMSE is the only means to measure the accuracy of regression models or is there any other technique?
Also, how to interpret the RMSE result is accurate or not?

For classification , there are lot of techniques like sensitivity, specificity, AUC etc…


Hi @shankarthebest,

Apart from RMSE, following metrics can be used to evaluate the regression model:

  • Mean Absolute Error (MAE) which is the mean of the absolute value of the errors:


  • Mean Squared Error (MSE) which is the mean of the squared errors:


RMSE tells us how far our predicted values are from the actual values. So lesser the RMSE value, better the predictions.