Loss Function, Data Science, Heartbeat, Data Science For Ml.
would always be better modeled using non-linear functions or tree-based models. This is where quantile loss and quantile regression come to the rescue as regression-based on quantile loss provides sensible prediction intervals even for residuals with non-constant variance or non-normal