Xiaomei Yang

Feature Learning With a Divergence-Encouraging Autoencoder for Imbalanced Data Classification

2018 · IEEE Access

Imbalanced data exists commonly in machine learning classification applications. Popular classification algorithms are based on the assumption that data in different classes are roughly equally distributed; however, extremely skewed data, with instances from one class …