Informational Paradigm, management of uncertainty and theoretical formalisms in the clustering framework: A review

Fifty years have gone by since the publication of the first paper on clustering based on fuzzy sets theory. In 1965, L.A. Zadeh had published “Fuzzy Sets” [335]. After only one year, the first effects of this seminal paper began to emerge, with the pioneering paper on clustering by Bellman, Kalaba, Zadeh [33], in which they proposed a prototypal of clustering algorithm based on the fuzzy sets theory

An interval type-2 fuzzy PCM algorithm for pattern recognition

The Possibilistic C-means (PCM) was proposed to overcome some of the drawbacks associated with the Fuzzy C-means (FCM) such as improved performance for noise data. However, PCM possesses some drawbacks such as sensitivity in the initial parameter values and to patterns that have relatively short distances between the prototypes. To overcome theses drawbacks, we propose an interval type-2 fuzzy approach to PCM by considering uncertainty in the fuzzy parameter m in the PCM algorithm. ��2009 IEEE