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
This metric does not have any parameters.
use Rubix\ML\CrossValidation\Metrics\SMAPE; $metric = new SMAPE();
- 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.