================== ==========================================================================================================================================================================================================
Subkey             Description                                                                                                                                                                                               
================== ==========================================================================================================================================================================================================
Use                Percentage of times Object (e.g. patient) resampling is used.                                                                                                                                             
Method             One of the methods adopted, see also imbalanced learn <https://imbalanced-learn.readthedocs.io/en/stable/api/>`_.                                                                                         
sampling_strategy  Sampling strategy, see also imbalanced learn <https://imbalanced-learn.readthedocs.io/en/stable/api/>`_.                                                                                                  
n_neighbors        Number of n_neighbors used in resampling. This should be (much) smaller than the number of objects/patients you supply. We sample on a uniform scale: the parameters specify the range (loc, loc + scale).
k_neighbors        Number of n_neighbors used in resampling. This should be (much) smaller than the number of objects/patients you supply. We sample on a uniform scale: the parameters specify the range (loc, loc + scale).
threshold_cleaning Threshold for cleaning of samples. We sample on a uniform scale: the parameters specify the range (loc, loc + scale).                                                                                     
================== ==========================================================================================================================================================================================================