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This page was last edited on 21 December 2024, at 20:13 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
This page was last edited on 21 December 2024, at 20:12 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
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Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...
For example, if the mean height in a population of 21-year-old men is 1.75 meters, and one randomly chosen man is 1.80 meters tall, then the "error" is 0.05 meters; if the randomly chosen man is 1.70 meters tall, then the "error" is −0.05 meters.
Mean absolute scaled error; Mean integrated squared error; Mean squared error; Mean squared prediction error; Minimum mean square error; N.
Margin of error; Market risk; McKay's approximation for the coefficient of variation; Mean absolute difference; Mean absolute error; Mean absolute percentage error; Mean absolute scaled error; Mean square quantization error; Mean squared displacement; Mean squared error; Mean squared prediction error; Medcouple; Median absolute deviation ...
In contrast to the mean absolute percentage error, SMAPE has both a lower and an upper bound. Indeed, the formula above provides a result between 0% and 200%. Indeed, the formula above provides a result between 0% and 200%.