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Materials for "New Findings from Explainable SYM-H Forecasting using Gradient Boosting Machines"
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Authors:

- Daniel Iong (University of Michigan, Ann Arbor)
- Yang Chen (University of Michigan, Ann Arbor)
- Gabor Toth (University of Michigan, Ann Arbor)
- Shasha Zou (University of Michigan, Ann Arbor)
- Tuija Pulkkinen (University of Michigan, Ann Arbor)
- Jiaen Ren (University of Michigan, Ann Arbor)
- Enrico Camporeale (University of Colorado, Boulder/NOAA Space Weather Prediction
  Center)
- Tamas Gombosi (University of Michigan, Ann Arbor)

Description of files
--------------------

generate_results.ipynb: Main Jupyter notebook file used to generate plots/tables in the manuscript

generate_results.py: Python file containing helper functions to generate results in _generate_results.ipynb_

results/: Directory with subdirectories named xgboost_[LEAD TIME]_[FEATURES]
containing results for the corresponding lead time and features. The directory
results/villaverde_et_al2021/ was downloaded from
https://zenodo.org/record/4562456#.YreaotLMJQ8. The files in the results/ directory are used in _generate_results.ipynb_.

    - contribs.pkl*: Pickle file containing feature contributions.
    - features.pkl*: Pickle file containing data used in plotting features used.
    - model/: Directory containing model used
    - model_configs/processed_data_configs: Directories containing config files for internal use.
    - shap_values.pkl: Pickle file containing SHAP values for predictions
    - X_test.pkl/y_test.pkl: Pickle files containing test data
    - ypred.pkl: Pickle file containing predictions

    *Note: We only use the files contribs.pkl and features.pkl from the
    xgboost_[LEAD_TIME]_es_dyn_pressure and xgboost_[LEAD_TIME]_es_dyn_pressure_no_symh
    subdirectories so they do not exist in the other subdirectories.

rmse_siciliano.csv/rmse_villaverde.csv/rmse_tbl_burton.pkl: CSV/Pickle files
containing a table of RMSE values from methods that we compared to in our manuscipt

stormtimes_siciliano.csv: CSV file containing storm times used for training/testing
models in manuscript