# Machine Learning Solar Wind Delay Propagation

**Authors**: 
  
  - Carsten Baumann; DLR Institute for Solar-Terrestrial Physics, carsten.baumann@dlr.de
  
  - Aoife McCloskey; DLR Institute for Solar-Terrestrial Physics, aoife.mccloskey@dlr.de (alt:aoifemccloskey91@gmail.com)

## Description

This repository contains the program code for the Solar wind propagation delay machine learning approach using decision trees.

This repo includes:

the database (delay_DST_learningset.pickle) and code for:

stratification of database and k fold cross validation of the ML algorithms,

hyperparameter optimization of the ML algorithms,

comparison with other propagation delay models,

realtime scenario, (basic train/test approach but ordered in time),

drop column feature importance,

Shapley values to explain the models,

plotting routines


the repo for writing a manuscript is found under publications