Research and improvement of clustering algorithm in data mining
Ren Jingbiao, Yin Shaohong · 2010
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.