A Survey of Forecast Error Measures

By M. Shcherbakov, A. Brebels, A. Tyukov, Timur Janovsky, Valeriy Anatol. 2013

557 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/435eb6e05fcda264c8c1e7fbcdee7116bb5b1424

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Alexei Botchkarev

Citations in the corpus

• Performance Metrics (Error Measures) in Machine Learning Regression, Forecasting and Prognostics: Properties and Typology (2018, methodology): “Shcherbakov et al (2013) presented a survey of more than twenty forecast error measures.”
• The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation (2021, unknown): “…similarly to what happened for binary classi fi cation, a plethora of performance metrics have been de fi ned and are currently in use for evaluating the quality of a regression model ( Shcherbakov et al., 2013 ; Hyndman & Koehler, 2006 ; Botchkarev, 2018b , Botchkarev, 2018a , Botchkarev, 2019 ).”