Using grid-clustering methods in data classification

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.