抄録
Shell clustering methods partition data sets into several shell-shape clusters by extracting local circles or ellipses as prototypes of clusters. This paper proposes hard c-regression models (HCRMs) for shell clustering. HCRMs successfully detect ellipses by using the hard clustering approach and random initialization.
