JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2009, Vol. 39 ›› Issue (5): 22-26.

• Articles • Previous Articles     Next Articles

Adaptive spectral clustering algorithm

  

  1. Department of Computer Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2009-06-16 Online:2009-10-16 Published:2009-10-16

Abstract:

Spectral clustering has been used to identify clusters that are non-linearly separable in input space, and usually outperforms traditional clustering algorithms. However, the performances of spectral clustering are severely dependent on values of the scaling parameter. In this paper, an adaptive spectral clustering (ASC) algorithm was proposed based on traditional spectral clustering, which can choose the scaling parameter automatically by using techniques similar to kernel selection. The new algorithm was compared to existing parameter selection based spectral clustering algorithms on both synthetic and UCI data sets, and the experimental results validate the effectiveness of the proposed algorithm.

Key words: adaptive; spectral clustering; parameter selecuion

No related articles found!
Viewed
Full text
330
HTML PDF
Just accepted Online first Issue Just accepted Online first Issue
0 0 0 0 0 330

  From Others local
  Times 29 301
  Rate 9% 91%

Abstract
1065
Just accepted Online first Issue
0 0 1065
  From Others local
  Times 1063 2
  Rate 100% 0%

Cited

Web of Science  Crossref   ScienceDirect  Search for Citations in Google Scholar >>
 
This page requires you have already subscribed to WoS.
  Shared   
  Discussed   
No Suggested Reading articles found!