In this paper, we show how one can take advantage of the stability and effectiveness of object data clustering algorithms when the data to be clustered are available in the form Of Mutual numerical relationships between pairs of objects. More precisely, we propose a new fuzzy relational algorithm, based on the popular fuzzy C-means (FCM) algorithm, which does not require any particular restriction on the relation matrix. We describe the application of the algorithm to four real and four synthetic data sets, and show that our algorithm performs better than well-known fuzzy relational Clustering algorithms on all these sets.

A new fuzzy relational clustering algorithm based on the fuzzy C-means algorithm

CORSINI, PAOLO;LAZZERINI, BEATRICE;MARCELLONI, FRANCESCO
2005-01-01

Abstract

In this paper, we show how one can take advantage of the stability and effectiveness of object data clustering algorithms when the data to be clustered are available in the form Of Mutual numerical relationships between pairs of objects. More precisely, we propose a new fuzzy relational algorithm, based on the popular fuzzy C-means (FCM) algorithm, which does not require any particular restriction on the relation matrix. We describe the application of the algorithm to four real and four synthetic data sets, and show that our algorithm performs better than well-known fuzzy relational Clustering algorithms on all these sets.
2005
Corsini, Paolo; Lazzerini, Beatrice; Marcelloni, Francesco
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/179237
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