Mean Absolute Error
Mean Absolute Error is a forecast verification metric that quantifies the average magnitude of prediction errors by computing the arithmetic mean of absolute differences between predicted and observed values across a set of forecasts.
4.5K
Publications
274K
Citations
16.1K
Authors
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Publications per year
2017–2026
2.6K
Variants
Mae
Parents
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Another look at measures of forecast accuracy
Rob J. Hyndman, Anne B. Koehler · International Journal of Forecasting · 2006 · 5.3K citations
Computing, Mathematics, Meteorology +16
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11 publications · 291 citations
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Chinese Academy of Sciences
Beijing, China
37 h-index
255 publications
11K citations

Centre National de la Recherche Scientifique
Paris, France
24 h-index
118 publications
6.3K citations
University of Chinese Academy of Sciences
Beijing, China
22 h-index
83 publications
2.8K citations
Georgia Institute of Technology
Atlanta, United States
21 h-index
51 publications
8.4K citations

University of Tehran
Tehran, Iran
21 h-index
67 publications
2.6K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
21 h-index
47 publications
2.1K citations
University College London
London, United Kingdom
21 h-index
64 publications
3.7K citations
Wuhan University
Wuhan, China
19 h-index
100 publications
3K citations
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81 publications · 16.7K citations
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56 publications · 3.6K citations
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JCTC · 55 publications · 3.8K citations
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62 publications · 3.4K citations
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67 publications · 4.1K citations
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