Using grid-clustering methods in data classification

Author

Grabusts, Peter ; Borisov, Arkady

Author_Institution

Decision Support Syst. Group, Riga Tech. Univ., Latvia

fYear

2002

fDate

2002

Firstpage

425

Lastpage

426

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Parallel Computing in Electrical Engineering, 2002. PARELEC '02. Proceedings. International Conference on

Print_ISBN

0-7695-1730-7

Type

conf

DOI

10.1109/PCEE.2002.1115319

Filename

1115319

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2605510