Title :
Using grid-clustering methods in data classification
Author :
Grabusts, Peter ; Borisov, Arkady
Author_Institution :
Decision Support Syst. Group, Riga Tech. Univ., Latvia
Abstract :
This paper examines grid-clustering method. Unlike the conventional methods, this method organizes the space surrounding the patterns. It uses a multidimensional grid data structure. The resulting block partitioning of the value space is clustered via a neighbor search. The mathematical description of the algorithms employed is given. Some case studies and ideas on how to use the algorithms are described.
Keywords :
data structures; pattern clustering; search problems; block partitioning; feature space; grid-clustering; multidimensional grid data structure; neighbor search; pattern clustering; Clustering algorithms; Data structures; Decision support systems; Information technology; Mathematical model; Multidimensional systems; Partitioning algorithms; Space technology; System identification; Uncertainty;
Conference_Titel :
Parallel Computing in Electrical Engineering, 2002. PARELEC '02. Proceedings. International Conference on
Print_ISBN :
0-7695-1730-7
DOI :
10.1109/PCEE.2002.1115319