Loss Function, Data Science, Heartbeat, Data Science For Ml.
MAE). The idea is to choose the quantile value based on whether we want to give more value to positive errors or negative errors. Loss function tries to give different penalties to overestimation and underestimation based on the value of the chosen quantile (γ). For example, a quantile loss