When training our approach, we perform exhaustive feature selection to determine which sub-set of the four sets of features (i.e., n-gram, duplicated Faulkner, path-based, and knowledge-based features) should be used.
we select the feature groups and learner jointly by performing cross validation on the training folds, choosing the combination yielding the highest average of micro and macro F-scores in each fold experiment.