# smape: Symmetric Mean Absolute Percentage Error In mfrasco/Metrics: Evaluation Metrics for Machine Learning

## Description

`smape` computes the symmetric mean absolute percentage error between two numeric vectors.

## Usage

 `1` ```smape(actual, predicted) ```

## Arguments

 `actual` The ground truth numeric vector. `predicted` The predicted numeric vector, where each element in the vector is a prediction for the corresponding element in `actual`.

## Details

`smape` is defined as two times the average of `abs(actual - predicted) / (abs(actual) + abs(predicted))`. Therefore, at the elementwise level, it will provide `NaN` only if `actual` and `predicted` are both zero. It has an upper bound of `2`, when either `actual` or `predicted` are zero or when `actual` and `predicted` are opposite signs.

`smape` is symmetric in the sense that `smape(x, y) = smape(y, x)`.

`mape` `mase`
 ```1 2 3``` ```actual <- c(1.1, 1.9, 3.0, 4.4, 5.0, 5.6) predicted <- c(0.9, 1.8, 2.5, 4.5, 5.0, 6.2) smape(actual, predicted) ```