Characterizing Imprecision in Multi-View Clustering Using Entropy-Weighted Low-Rank Evidential C-Means

The core message of this article is to propose a multi-view evidential clustering method, called MvLRECM, that can characterize uncertainty and imprecision in multi-view data by allowing objects to belong to different clusters with varying degrees of support.