Title :
Efficient global clustering using the greedy elimination method
Author :
Chan, Z.S.H. ; Kasabov, N.
Author_Institution :
Knowledge Eng. Discovery & Res. Inst., Auckland Univ. of Technol., New Zealand
Abstract :
A novel global clustering method called the greedy elimination method is presented. Experiments show that the proposed method scores significantly lower clustering errors than the standard K-means over two benchmark and two application datasets, and it is efficient for handling large datasets.
Keywords :
greedy algorithms; pattern clustering; statistical analysis; application datasets; clustering errors; dataset handling; global clustering method; greedy elimination method; standard K-means method; statistical analysis;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:20046785
