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"Anti-Bayesian" flat and hierarchical clustering using symmetric quantiloids
2017
Information Sciences
A myriad of works has been published for achieving data clustering based on the Bayesian paradigm, where the clustering sometimes resorts to Naïve-Bayes decisions. Within the domain of clustering, the Bayesian principle corresponds to assigning the unlabelled samples to the cluster whose mean (or centroid) is the closest. Recently, Oommen and his co-authors have proposed a novel, counter-intuitive and pioneering PR scheme that is radically opposed to the Bayesian principle. The rational for
doi:10.1016/j.ins.2017.08.017
fatcat:nyenjhhffjax5lwozlvhcigioa