Talk:Root-mean-square deviation

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"Regression ratio"/"learning ratio"? When measuring the performance of a predictive model (e.g. regression) you can divide the RMSD by the standard deviation of the target data. When greater than or equal to one you have no learning better than the simple guessing of the mean of the data. When less than one, the prediction is more informative than just the mean. My question is: what is this measure commonly called? Uncoolbob 21:05, 15 January 2007 (UTC)

Update: colleagues are suggesting "Normalized RMSE" (or "Normalised RMSD"). Is this in wide enough use to add to the article? Uncoolbob 16:15, 16 January 2007 (UTC)

It is certainly wide enough in my field (Bioinformatics) to be useful and pertinent. The is a lot more to the story of "RMSD" than we have in this article. It could also use a lot more math theory. I also have a programme I wrote in C for calculating RMSD (it is impressively fast) and will upload the code to this site soon.--Thorwald 01:52, 17 January 2007 (UTC)

How does one interpret the RMSE value? If some results from my research yield a RMSE of, say 0.01 when comparing to an idealised estimator, what does that tell me? How can one tell if the RMSE is high or low? I think this information would be useful in this article. --Utsutsu (talk) 01:29, 3 February 2010 (UTC)

What are the xmin and xmax to be used for the normalized RMSE computation? Should it be the range of the first variable, the second or both? -- Danielgenin (talk) 17:22, 28 December 2010 (UTC)

This is not a good article. The words are unnecessarily wordy - oblong for example. There is also unnecessary complexity such as the use of vectors to help explain the concept. The article should be simplified. — Preceding unsigned comment added by 142.52.81.11 (talk) 05:10, 6 September 2012 (UTC)