For all experiments the first level folder hierarchy indicates the method used. Where parameter tuning is performed, the second level folders indicate algorithm parameters . Each experiment output is stored in a xz compressed text file in JSON format. In experiments measuring the learning curves ( training-* ), each results file describes: * experiment setup (algorithm, number of subsets, down-sampled class size)* list of training set sizes * performance measure statistics for all subsets at each training size (flat list) including min, median and max score, and median deviation from median (mad), given for both test and training set instance