I see that, as of v. 1.1, MLLib supports regression and classification tree models. I assume this means that it uses a squared-error loss function for the first and logistic cost function for the second. I don't see support for quantile regression via an absolute error cost function. Or am I missing something?
If, as it seems, this is missing, how do you recommend to implement it? Alex
