Online active learning method for multi-class imbalanced data stream

A comprehensive sample weighting method based on cross-entropy and margin values is proposed to weight each incoming sample in the data stream according to its classification difficulty and importance, which aims to enhance the learning ability of the classifier for important samples and a margin matrix label request strategy based on class imbalance ratio is proposed.