Previous work (Estabrooks et al., 2004) reported that under-sampling of the majority class (predominant sense) has been proposed as a good means of increasing the sensitivity of a classifier to the minority class (infrequent sense).
in our active learning experiments, under-sampling is apparently worse than ordinary, over-sampling and our BootOS.