PyAF can be configured to use MAPE, SMAPE and many other performance measures to perform model selection.
MAPE and SMAPE are sensitive to zero values in the signal/forecast.
Differentiable SMAPE (Suilin, 2017) is a recent variant of the SMAPE that makes it not only smooth, differentiable but also more resistant to zero values.
PyAF can be configured to use MAPE, SMAPE and many other performance measures to perform model selection.
MAPE and SMAPE are sensitive to zero values in the signal/forecast.
Differentiable SMAPE (Suilin, 2017) is a recent variant of the SMAPE that makes it not only smooth, differentiable but also more resistant to zero values.
Found in : https://cbergmeir.com/talks/FFDS_ACML2020.pdf (page 104)
Original source code : https://www.kaggle.com/code/asuilin/smape-variants/notebook https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39529
To be included in the next PyAF release (5.0, expected on 2023-07-14).