SMAPE#
Symmetric Mean Absolute Percentage Error (SMAPE) is a scale-independent regression metric that expresses the relative error of a set of predictions and their labels as a percentage. It is an improvement over the non-symmetric MAPE in that it is both upper and lower bounded.
Note
In order to maintain the convention of maximizing validation scores, this metric outputs the negative of the original score.
Estimator Compatibility: Regressor
Output Range: -100 to 0
Parameters#
This metric does not have any parameters.
Example#
use Rubix\ML\CrossValidation\Metrics\SMAPE;
$metric = new SMAPE();
References#
-
V. Kreinovich. et al. (2014). How to Estimate Forecasting Quality: A System Motivated Derivation of Symmetric Mean Absolute Percentage Error (SMAPE) and Other Similar Characteristics. ↩
Last update:
2021-03-03