Open m1sta opened 3 years ago
@m1sta Thanks for the question.
Choosing between the two depends on the problem at hand I'd say:
So in summary, both approaches allow to go beyond modelling the conditional mean. But the model of choice depends on your problem at hand.
Hope that helps. Feel free to come back in case of further questions.
Would you be able to shed some light on when to use the distribution fitting features of CatBoostLSS versus the quantile regression feature of the standard CatBoost package?