Title :
Research and improvement of clustering algorithm in data mining
Author :
Jingbiao, Ren ; Shaohong, Yin
Author_Institution :
Tianjin Polytech. Univ., Tianjin, China
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;
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
DOI :
10.1109/ICSPS.2010.5555239