  We examine learning offensive content on Twitter with limited, imbalanced
data. For the purpose, we investigate the utility of using various data
enhancement methods with a host of classical ensemble classifiers. Among the 75
participating teams in SemEval-2019 sub-task B, our system ranks 6th (with
0.706 macro F1-score). For sub-task C, among the 65 participating teams, our
system ranks 9th (with 0.587 macro F1-score).
