Ernesto López Fune

I would like as well to make a suggestion. Could you please as well include a Lasso regularization term into the Linear Multi-Task Logistic Regression and Linear SVM Loss Functions...

Thanks for the quick answer. I believe ElasticNet will give the users more flexibility to optimize survival models.

Yes, a line of code like this is perfect! `loss += l2_reg * torch.sum(w * w) / 2. + (1.0 - l2_reg) * torch.sum(torch.abs(w))` I tried once to change it...

Well, indeed, there is the need to introduce a new parameter namely `penalizer` or something like this, which will be the "penalizer" of the model. `l2_reg` will be to choose...

I have Python 3.8.6

Thanks, I m trying to solve this problem that it is driving me crazy

I just tried to maximize the C statistics for the Random Survival Forest model with respect to the hyper-parameters and it takes more than three days to give a result....