Záznam dôkazov metódy

Mean Absolute Percentage Error

Mean Absolute Percentage Error measures prediction accuracy as a percentage relative to actual values, expressing errors in units that are scale-independent and interpretable across datasets. Formalized by J. Scott Armstrong in 1985, MAPE is widely used in forecasting, supply chain, and business analytics where results must be communicated as percentage accuracy.

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Zdrojový záznam

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Taxonomický záznam metódy · mcdm / model-evaluation

Armstrong, J. S. (1985). Long-range forecasting: from crystal ball to computer (2nd ed.). New York: John Wiley & Sons. · ISBN 978-0471082010
Hyndman, R. J., & Koehler, A. B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), 679-688. · DOI 10.1016/j.ijforecast.2006.03.001
Kim, S., & Kim, H. (2016). A new metric of absolute percentage error for intermittent demand forecasts. International Journal of Forecasting, 32(3), 669-679. · DOI 10.1016/j.ijforecast.2015.12.003

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Súvisiace metódy

Vygenerované z grafu metód a zobrazené ako vzťahy navrhnuté strojom – nevyplýva z nich žiadne tvrdenie o dôkaze.

Same method familyMean Absolute Errormachine-suggested · Relational suggestion, not evidence.Same method familyMean Absolute Scaled Errormachine-suggested · Relational suggestion, not evidence.Same method familyRoot Mean Squared Errormachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSymmetric MAPEmachine-suggested · Relational suggestion, not evidence.