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Percentage error; Mean absolute percentage error; Mean squared error; Mean squared prediction error; Minimum mean-square error; Squared deviations; Peak signal-to-noise ratio; Root mean square deviation; Errors and residuals in statistics; References. Khan, Aman U.; Hildreth, W. Bartley (2003). Case studies in public budgeting and financial ...
Confusingly, sometimes when people refer to wMAPE they are talking about a different model in which the numerator and denominator of the wMAPE formula above are weighted again by another set of custom weights .
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Mean percentage error; Symmetric mean absolute percentage error; References This page was last edited on 2 April 2024, at 22:32 (UTC). ...
Thus the MSE results from pooling all these sources of error, ... While 50% is a very common definition for CEP, the circle dimension can be defined for percentages.
In contrast to the mean absolute percentage error, SMAPE has both a lower bound 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%.
One can then also calculate the mean square of the model by dividing the sum of squares of the model minus the degrees of freedom, which is just the number of parameters. Then the F value can be calculated by dividing the mean square of the model by the mean square of the error, and we can then determine significance (which is why you want the ...
Definition and basic properties. The MSE either assesses the quality of a predictor (i.e., a function mapping arbitrary inputs to a sample of values of some random variable), or of an estimator (i.e., a mathematical function mapping a sample of data to an estimate of a parameter of the population from which the data is sampled).