Machine learningGrey systems

Grey Clustering: Whitenization-Based Classification Under Uncertainty

Grey Clustering is a classification method from grey systems theory that assigns objects to predefined grey classes using whitenization weight functions. Developed within the framework of Deng Julong's grey system theory and systematized by Sifeng Liu, it is particularly suited for situations involving small sample sizes, incomplete information, or uncertain data—conditions common in engineering assessments, environmental monitoring, and socioeconomic evaluation. The method quantifies how strongly each object belongs to each grey class and makes a crisp assignment based on maximum clustering coefficients.

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Sources

  1. Liu, S., & Lin, Y. (2010). Grey Systems: Theory and Applications. Springer. ISBN: 978-3-642-13937-6

Related methods

ScholarGateGrey Clustering (Grey Clustering (Grey Incidence / Whitenization)). Retrieved 2026-06-04 from https://scholargate.app/en/soft-computing/grey-clustering