An Imbalance-Resilient Deep Classification Framework for Reliable Analytics in Real-World Data Streams
Data streams in the real world often display severe class imbalance, with a critical under-representation of minority-class instances, resulting in biased and unreliable classification results from conventional deep learning frameworks. We introduce a new Imbalance-Resilient Deep Classification Framework that is define...