Michael Mayer

I played a bit with the code. Without passing `weight`s, I could not reproduce the problem. However, even with quite low weights (imbalance 2 or 3), the problem remained.

A Kaplan-Meier curve is a purely descriptive method. Thus it is unclear how it should be related to a statistical model.

I suggest to keep `xgboost()` and `predict()` as they are and instead call the new functions differently, e.g. `xgboost2()` and `predict2()`. Too much code would break when changing the main...

@madprogramer In the upcoming v.0.4.0 of "shapviz", I have written from scratch the beeswarm visualization in `sv_importance()` . Since it is now built on top of `geom_point()`, the beeswarm plot...

In the question, you use both terms "prediction interval" and "confidence interval". These are completely different. - A *prediction interval* is a statement about the random variable $Y | X...

CI and PI are well-defined concepts. It does not make sense to redefine them or calling a CI a PI. Maybe you are indeed looking for a CI for the...

These are interesting ideas. It would be great to have a simulation study where we would investigate the coverage probability of such intervals! Typical question would be: - How close...

@tiagoleonmelo Thanks for the additional thoughts. >Ultimately, I suppose we can generate the "official" confidence intervals by training separate models, and comparing the generated CIs with our experimental CIs Interesting...

I am not 100% certain. Maybe you could start with a known, deterministic model.

I am only talking about confidence intervals as prediction intervals are completely irrelevant in classification. With CIs, you would calculate the proportion of intervals that cover the true conditional probability...