Title :
Data Clustering of Tolerance Space in MATLAB
Author :
Sun, Fu-Shing ; Tzeng, Chun-Hung
Author_Institution :
Dept. of Comput. Sci., Ball State Univ., Muncie, IN
Abstract :
This paper introduces an abstract data clustering model and its implementation in MATLAB. The similarity in the model is an arbitrary reflexive and symmetric binary relation, called a tolerance relation. A space with a tolerance relation is called a tolerance space. This paper considers representative clusterings of a tolerance space. Such a clustering is a set of representatives in the space and each element in the space is similar to one of the representatives. In general, a representative clustering is not a partition of the space. A heuristic method to compute a sub-minimal representative clustering is implemented in MATLAB. Finally, the paper demonstrates the clusterings using an example dataset
Keywords :
mathematics computing; pattern clustering; MATLAB; abstract data clustering model; heuristic method; reflexive binary relation; subminimal representative clustering; symmetric binary relation; tolerance relation; tolerance space clusterings; Clustering algorithms; Clustering methods; Computer science; MATLAB; Mathematical model; Partitioning algorithms; Sun;
Conference_Titel :
Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2006. SNPD 2006. Seventh ACIS International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
0-7695-2611-X
DOI :
10.1109/SNPD-SAWN.2006.27