Showing papers by "Boris Mirkin published in 2000"
07 May 2000
TL;DR: The FCMP framework is extended to a number of clustering criteria, and the FCMP properties on fitting the underlying proposed model from which data is generated are studied.
Abstract: The multiple prototype fuzzy clustering model (FCMP), introduced by Nascimento, Mirkin and Moura-Pires (1999), proposes a framework for partitional fuzzy clustering which suggests a model of how the data are generated from a cluster structure to be identified. In the model, it is assumed that the membership of each entity to a cluster expresses a part of the cluster prototype reflected in the entity. In this paper we extend the FCMP framework to a number of clustering criteria, and study the FCMP properties on fitting the underlying proposed model from which data is generated. A comparative study with the fuzzy c-means algorithm is also presented.
82 citations
13 Jul 2000
TL;DR: The fuzzy clustering proportional membership proposes a model of how data are generated from a cluster structure to be identified and expresses the proportion of the cluster's prototype reflected in the entity (proportional membership).
Abstract: The fuzzy clustering proportional membership (FCPM) proposes a model of how data are generated from a cluster structure to be identified. Cluster prototypes and membership functions are meaningful in the context of the model. In particular, the membership of an entity to a cluster expresses the proportion of the cluster's prototype reflected in the entity (proportional membership). We explore the notion of proportional membership and compare it against the fuzzy c-means (FCM) distance membership. The ability of FCPM to reveal the underlying clustering model of data has been studied and a comparison with FCM had also been performed.
7 citations