Geometrically interpretable Variance Hyper Rectangle learning for pattern classification

Jie Sun, Huamao Gu, Haoyu Peng, Yili Fang, Xun Wang

Abstract: Highlights•VHR has strong geometric interpretability, and is much reliable and trustworthy.•VHR can provide a clear range of values in each direction for a category of data.•VHR naturally supports incremental learning without any extra processing.•VHR has great performance and stability, and is able to handle big data.