Memetic Differential Evolution Methods for Semi-Supervised Clustering

arXiv:2403.04322v1 Announce Type: cross
Abstract: In this paper, we deal with semi-supervised Minimum Sum-of-Squares Clustering (MSSC) problems where background knowledge is given in the form of instance-level constraints. In particular, we take into account "must-link" and "cannot-link" constraints, each of which indicates if two dataset points should be associated to the same or to a different cluster. The presence of such constraints makes the problem at least as hard as its unsupervised version: it is no more true that each …

abstract arxiv clustering constraints cs.lg cs.ne dataset deal differential evolution form instance knowledge math.oc paper semi-supervised squares type