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RMSE of vs r-square of

These two phrases are not directly comparable as they refer to different statistical metrics. "RMSE" stands for Root Mean Square Error, which is a measure of the differences between values predicted by a model and the actual values observed. On the other hand, "R-square" is a statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable. Therefore, the choice between the two depends on the specific context and the type of analysis being conducted.

Last updated: March 17, 2024

RMSE of

This phrase is correct when referring to the Root Mean Square Error (RMSE) of a model's predictions.

This phrase is used to specify the RMSE value of a model, indicating the average difference between predicted values and actual values.
  • Apr 16, 2013 ... For a datum which ranges from 0 to 1000, an RMSE of 0.7 is small, but if the range goes from 0 to 1, it is not that small anymore. However ...
  • [EDIT: 20110610 00:17 CDT - reformat - WDR]. So i was looking online how to check the RMSE of a line. found many option, but I am stumble about something,.
  • The RMSE of a model prediction with respect to the estimated variable Xmodel is defined as the square root of the mean squared error: where Xobs is observed ...
  • You read that a set of temperature forecasts shows a MAE of 1.5 degrees and a RMSE of 2.5 degrees. What does this mean? Choose the best answer: ...

r-square of

This phrase is correct when referring to the R-square value, which measures the goodness of fit of a regression model.

This phrase is used to specify the R-square value of a regression model, indicating how well the independent variables explain the variability of the dependent variable.
  • Aug 21, 2011 ... Like you I have often heard that in sociology an R Square of 0.05 is acceptable. I sometimes wonder if that truly can be correct, or does it reflect ...
  • Feb 16, 2014 ... Can R Square of .15 of a full model in SEM be acceptable? Is it acceptable in a PhD. thesis? If yes then please provide some references to ...
  • Feb 13, 2013 ... thanks a lot for the post. there is no mention how to compute r-square of multiple imputed regression logistic. what is the best way for it ? thanks.
  • Does a low R-square make my decision tree model unreliable? Can adjusted R square of a regression be negative? Can I use adjusted R-squared to compare ...

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