Open moghadas76 opened 8 months ago
Hi,
Are MASE and MAE(in the literature) metric are consistent?
def mase( target: np.ndarray, forecast: np.ndarray, seasonal_error: float, ) -> float: r""" .. math:: mase = mean(|Y - \hat{Y}|) / seasonal\_error See [HA21]_ for more details. """ return np.mean(np.abs(target - forecast)) / seasonal_error
My implementation for MAE:
def mae( target: np.ndarray, forecast: np.ndarray, seasonal_error: float, ) -> float: r""" .. math:: mase = mean(|Y - \hat{Y}|) See [HA21]_ for more details. """ return np.mean(np.abs(target - forecast))
Hi,
Are MASE and MAE(in the literature) metric are consistent?
def mase( target: np.ndarray, forecast: np.ndarray, seasonal_error: float, ) -> float: r""" .. math:: mase = mean(|Y - \hat{Y}|) / seasonal\_error See [HA21]_ for more details. """ return np.mean(np.abs(target - forecast)) / seasonal_errorMy implementation for MAE:
def mae( target: np.ndarray, forecast: np.ndarray, seasonal_error: float, ) -> float: r""" .. math:: mase = mean(|Y - \hat{Y}|) See [HA21]_ for more details. """ return np.mean(np.abs(target - forecast))