Using Supervised Convex Clustering for Two Dimensional Clusters
Title: Supervised Convex ClusteringAuthors & Year: Minjie Wang, Tianyi Yao, and Genevera I. Allen (2023)Journal: Biometrics [DOI: 10.1111/biom.13860]Review Prepared by Edmond Sanou Clustering is a common way for computers to group together similar things when we don’t already know the categories. The problem is that the groups it finds are sometimes hard to make sense of. In real life, though, we often have extra pieces of information, like doctors’ opinions or other clues, that, while imperfect, can help guide the grouping. The authors Wang, Yao, and Allen. created a new method called supervised convex clustering (SCC), which combines both the raw data and these extra guiding clues. This makes the discovered groups easier to interpret and more meaningful scientifically. They also adapted the method so it can handle different kinds of extra information and even look for patterns in two dimensions at once (biclusters). When they tested SCC, including on…