From 5c4c94f5d4f02b664d72f0af5cfbf9d670afba75 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Alexander=20M=C3=A4rz?= <41187941+StatMixedML@users.noreply.github.com> Date: Wed, 2 Aug 2023 10:00:00 +0200 Subject: [PATCH] Update README.md --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 68f066ca..e6e7ffbc 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,6 @@ + + +# XGBoostLSS - An extension of XGBoost to probabilistic forecasting

![Python package](https://github.com/StatMixedML/XGBoostLSS/workflows/CI%20of%20Package/badge.svg) @@ -5,9 +8,6 @@

- - -# XGBoostLSS - An extension of XGBoost to probabilistic forecasting We propose a new framework of XGBoost that predicts the entire conditional distribution of univariate and multivariate responses. In particular, **XGBoostLSS** models all moments of a parametric distribution, i.e., mean, location, scale and shape (LSS), instead of the conditional mean only. Choosing from a wide range of continuous, discrete, and mixed discrete-continuous distribution, 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. ## Features