More interestingly, it can be seen that for predicting VFORM:GER i.e, continuous verb forms, the lowest weighted features are those morphological transformations that substitute "ing" with something else.
if there exists an edge between the words studying and study, containing the feature: suffix:ing:{null}, the model would correctly predict that studying is VFORM:GER as study is not so and the negative feature weight can flip the label values.