Just writing this to share which target functions you use the most when training your models. I was thinking of customizing an Objective Function for boosted models in order to beat the common methods already developed. I know Spearman’s correlation is non-differentiable due to sort and rank steps, but I found some references to try to deal with these problems:

I’ve tried to use SoDeep loss functions when training my MLPs and it was a complete disaster. So it would be nice to hear some tips from you all. Do you keep going with RMSE, MSE, MAE. MAPE, LOGLOSS…?