Timeline for testing linear regression model efficiency
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Dec 2, 2015 at 9:31 | comment | added | BGreene | Yes. It is a scalar value. A perfectly fitted model would have RMSE of 0. | |
| Sep 24, 2015 at 20:57 | comment | added | KingPolygon | I know this is a bit old, but just to double check, the RMSE is a scalar value correct? And the optimal value would be 0? | |
| May 11, 2012 at 13:57 | comment | added | BGreene | Yes, thats correct. | |
| May 11, 2012 at 13:37 | vote | accept | ACEG | ||
| May 11, 2012 at 13:37 | comment | added | ACEG | Thanks a lot for the suggestion, this is exactly what I was looking for! So I would do sqrt(sum((predicted_i - actual_i)^2)/#samples), where i=1..#samples? | |
| May 11, 2012 at 13:28 | history | answered | BGreene | CC BY-SA 3.0 |