I have fitted a lgb_model and am experimenting with the backtest() method from darts. Just to confirm, the output is 5.7%, the MAPE correct?
from darts.models.forecasting.lgbm import LightGBMModel
lgb_model = LightGBMModel(lags=30)
lgb_model.fit(val)
# Backtest the model
backtest_results = lgb_model.backtest(series=val)
# Print the backtest results
print(backtest_results)
output:
...
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf
5.701803383509749
Yes, the output is interpreted as a percent, 5.7% in this case.
Looking at the darts documentation for the backtest() function, the default metric is MAPE. And looking at the actual darts code for the mape() function:
100.0 * np.mean(np.abs((y_true - y_hat) / y_true))
The 100 in the beginning means the value has already been converted to a percent for you, thus a 5.7% MAPE is the correct interpretation.