Fig. 4

The evaluation procedure for each task. For each cell type and feature set combination, 20-fold cross-validation is performed and the MAP across all 20 folds is returned. At each evaluation, a gradient boosted decision tree classifier is trained on 18 of the folds, convergence is monitored based on performance on a 19th fold, and the performance of the resulting model is evaluated on the 20th fold