These folders contain .json output files, which contain the results and optimal hyperparameters for each model, for the experiments done in this work. The general steps for reproducing a result is importing the SPA package and running SPA.main_SPA() with the hyperparameters recorded in a .json file.

For example, to reproduce the results within the "2 - Multicollinearity/multicollinear_1000x2-data_1to10-range_123456789-seed_(0,0.4)-ynoise_(0,0.1)-Xnoise_LASSO.json" file, one can run
SPA.main_SPA('multicollinear_1000x2-data_1to10-range_123456789-seed_(0,0.4)-ynoise_(0,0.1)-Xnoise.csv', cv_method = 'KFold', model_name = ['EN'], l1_ratio = [1])

To avoid having to run cross-validation over each combination of hyperparameters, one can also pass the optimal hyperparameters found in a .json file to SPA.main_SPA()
