Title :
A semi-fuzzy collaborative algorithm for cluster seeking
Author :
Fajr, Rkia ; Arafi, Ayoub ; Safi, Youssef ; Bouroumi, Abdelaziz
Author_Institution :
Ben M´sik Fac. of Sci., Inf. Process. Lab., Univ. Hassan II Mohammedia - Casablanca (UH2MC), Casablanca, Morocco
Abstract :
In this paper, we present a semi-fuzzy collaborative algorithm for detecting the optimal number of clusters in a given data set of unlabeled objects. This algorithm is based on a measure of inter-points similarity that allows the detection and creation of clusters, plus a measure of ambiguity that allows collaboration between clusters during their formation. The algorithm also provides a matrix of optimized prototypes representing all the detected clusters. The performance of the proposed method is demonstrated through three examples of test data.
Keywords :
fuzzy set theory; pattern clustering; cluster seeking; interpoints similarity; semifuzzy collaborative algorithm; Irrigation; ambiguity measure; cluster analysis; collaboration of clusters; fuzzy clustering; similarity measure;
Conference_Titel :
Intelligent Systems: Theories and Applications (SITA), 2013 8th International Conference on
Conference_Location :
Rabat
Print_ISBN :
978-1-4799-0297-2
DOI :
10.1109/SITA.2013.6560795
