Update README.md

Author: StatMixedML

README.md

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 <img align="right" width="156.5223" height="181.3" src="../master/figures/LightGBMLSS.png">
 
 
-# LightGBMLSS - An extension of LightGBM to probabilistic forecasting
+# LightGBMLSS - An extension of LightGBM to probabilistic modelling and prediction
 We propose a new framework of LightGBM that predicts the entire conditional distribution of a univariate response variable. In particular, **LightGBMLSS** 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 distributions, modelling and predicting the entire conditional distribution greatly enhances the flexibility of LightGBM, as it allows to create probabilistic forecasts from which prediction intervals and quantiles of interest can be derived.
 
 ## Features