I need to calculate features importance for my LightGBM Booster model. However, I cannot understand how are the values for feature importances obtained when using 'gain' type.
The docs say:
If "gain", result contains total gains of splits which use the feature.
I am using MAE objective and its initial value (absolute difference between mean value and each object) on the train sample equals 36.82; sum of all absolute errors equals 33200. However, the sum of all feature importances is about 139124, which is much greater. Could anyone share the formula, thanks.