Model training. We use the Optuna package for hyper-parameters optimization, limiting the search space for the single-and multi-label models to the values shown (Table ). We train the two models using different metrics. For the single-label model we use the categorical accuracy 19 whereas for the multi-label model we use the Label Ranking Average Precision (LRAP) score as implemented in Scikit-Learn 20 (see below).