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.
MethodMind'de açSoonVideoSoon
Tam yöntemi oku
Members only
Sign inSign in with a free account to read this section.
Sources
- Liu, S., & Lin, Y. (2010). Grey Systems: Theory and Applications. Springer. ISBN: 978-3-642-13937-6