How to characterize imprecision in multi-view clustering?

arXiv:2404.04970v1 Announce Type: new
Abstract: It is still challenging to cluster multi-view data since existing methods can only assign an object to a specific (singleton) cluster when combining different view information. As a result, it fails to characterize imprecision of objects in overlapping regions of different clusters, thus leading to a high risk of errors. In this paper, we thereby want to answer the question: how to characterize imprecision in multi-view clustering? Correspondingly, we propose a multi-view low-rank evidential c-means …

abstract arxiv cluster clustering cs.lg data information object objects risk singleton type view