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Nøjagtighed×Middelfejl (MAE)×
FagområdeModelevalueringModelevaluering
FamilieMCDMMCDM
Oprindelsesår20th century1799
OphavspersonHistorical statistical foundationsPierre-Simon Laplace
TypeEvaluation metricRobust distance-based metric
Oprindelig kildeFawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. DOI ↗Laplace, P. S. (1799). Traité de Mécanique Céleste. Paris: J.B.M. Duprat. link ↗
AliasserOverall Accuracy, Correct Classification RateMAE, L1 error, mean absolute deviation
Relaterede53
ResuméAccuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures how often the classifier makes correct predictions overall, regardless of class.Mean Absolute Error is a robust metric that measures the average absolute magnitude of prediction errors in regression models. Dating back to Pierre-Simon Laplace's work on observational errors (1799), MAE quantifies typical prediction deviation by averaging the absolute differences between observed and predicted values.
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ScholarGateSammenlign metoder: Accuracy · Mean Absolute Error. Hentet 2026-06-18 fra https://scholargate.app/da/compare