Time Series Analysis and Sales Forecasting for Automotive

Time Series Analysis #15

def mean_percentage_error(y_true, y_pred):
    return 100*np.mean((y_true - y_pred) / y_true)

print('MAE: \t{0:.1f}'.format(mean_absolute_error(test, forecasts)))
print('MSE: \t{0:.1f}'.format(mean_squared_error(test, forecasts)))
print('RMSE: \t{0:.1f}'.format(np.sqrt(mean_squared_error(test, forecasts))))
print('MAPE: \t{0:3.4f} %'.format(mean_percentage_error(test, forecasts)))