DocumentCode
1708608
Title
Research and improvement of clustering algorithm in data mining
Author
Jingbiao, Ren ; Shaohong, Yin
Author_Institution
Tianjin Polytech. Univ., Tianjin, China
Volume
1
fYear
2010
Abstract
This paper is a cluster analysis algorithm research carried out based on the existing data mining, which focuses on the current popular and commonly used K-means algorithm, and presents an improved K-harmonic means clustering algorithm through using a new distance measure. Through the regulation of distance metric parameters can achieve better clustering effects than the traditional K-harmonic means, and has an advantage both in run time and number of iterations.
Keywords
data mining; pattern clustering; K-harmonic means clustering algorithm; cluster analysis algorithm; data mining; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Data mining; Heuristic algorithms; Partitioning algorithms; Signal processing algorithms; K-means algorithm; clustering analysis; data mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Systems (ICSPS), 2010 2nd International Conference on
Conference_Location
Dalian
Print_ISBN
978-1-4244-6892-8
Electronic_ISBN
978-1-4244-6893-5
Type
conf
DOI
10.1109/ICSPS.2010.5555239
Filename
5555239
Link To Document