Current position: Home >> Scientific Research >> Paper Publications

A Hybrid Clustering Algorithm Based on Dimensional Reduction and K-Harmonic Means

Release Time:2019-03-11  Hits:

Indexed by: Conference Paper

Date of Publication: 2008-10-12

Included Journals: Scopus、CPCI-S、EI

Page Number: 11368-+

Key Words: Clustering Algorithm; K-harmonic Means; Principal Component Analysis

Abstract: Clustering analysis is an active and challenge research direction in the field of data mining. In this paper we propose a new clustering algorithm based on dimensional reduction approach and K-harmonic means algorithm. Numerical results illustrate that the new hybrid clustering algorithm has advantages in the computation time, iteration numbers and clustering results in most cases, and it is also an algorithm which is suitable for large scale data sets.

Prev One:An Improved BA Model Based on the PageRank Algorithm

Next One:Gaussian moments for noisy unifying model