A novel method for adaptive determination clusters number based on N-order nearest neighbor

Author

Hong Zhen ; Yu Li ; Zhang Guijun

Author_Institution

Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou, China

fYear

2010

fDate

29-31 July 2010

Firstpage

3007

Lastpage

3011

Abstract

For problem of determining clusters number in K-Means, it was proposed a method for adaptively determining value of K based on N-order nearest-neighbor analysis. By calculation of N-order shortest distance between neighbors of various points, it was analyzed the distribution of current random sample data and get all step-points through numerical calculation to determine final K adaptively in case of lacking priori knowledge. Theoretical analysis and numerical simulation results show the effectiveness and reliability, it always has role of guidance for good results of clustering in K-Means.

Keywords

pattern clustering; statistical analysis; N-order nearest neighbor; adaptive determination clusters number; current random sample data; k-means; lacking priori knowledge; n-order nearest-neighbor analysis; n-order shortest distance; numerical calculation; numerical simulation; theoretical analysis; Classification algorithms; Clustering algorithms; Mathematical model; Pattern recognition; Presses; Signal processing algorithms; Adaptive; Clustering Analysis; K-Means Algorithm; N-order Nearest-neighbor;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (CCC), 2010 29th Chinese

Conference_Location

Beijing

Print_ISBN

978-1-4244-6263-6

Type

conf

Filename

5573321