StatMixedML / XGBoostLSS

What it does

We introduce a comprehensive framework that models and predicts the full conditional distribution of univariate and multivariate targets as a function of covariates. Choosing from a wide range of continuous, discrete, and mixed discrete-continuous distributions, modelling and predicting the entire conditional distribution greatly enhances the flexibility of XGBoost, as it allows to create probabilistic forecasts from which prediction intervals and quantiles of interest can be derived.