Stochastic13

@milot-mirdita Thanks! I think this particular script serves me better than the one you cited. I do have a simple work-around which works perfectly well in my case (i.e. for...

@hcho3 I can post the main part of training script and the output. There is a large section of preprocessing and setting up the CV that I am skipping. Also...

@hcho3 I understand. The data is confidential unfortunately. Here's a reproducible example I recreated with random data: ``` import numpy as np import pandas as pd import xgboost as xg...

@hcho3 I can also try with similar random datasets with different censoring extents, if that sounds like something that helps narrow down the problem. I was just worried if I...

@trivialfis The increase doesn't have to be large either for the error, in case it helps. The following has the same error after 85 iterations, but both the `train` and...

@SandyBy Not directly, unfortunately. Had to change the data processing to get different results. Not much success with other implementations either. See if [scikit-survival](https://pypi.org/project/scikit-survival/) helps you since it has gradient-boosted...