Abstract
In scenarios of continuous data streams, classification faces challenges that batch learning does not, such as concept evolutions and concept drifts, so novelty detection is a necessary task. Multi-label classification in continuous data streams, still little investigated, brings even more challenges, especially in contexts with infinite latency of labels. However, ensembles of classifier…