摘要
说明聚类算法在数据挖掘中的作用,并结合实际数据的特点,采用一种新的模糊聚类算法。该算法在事先不知聚类数的情况下,能够确定聚类数及中心点。同时,能够消除噪声对于数据的影响,适合较大规模的数据,方便进一步的数据挖掘。对实际通信信号的实验结果表明该方法是实效的。
The effect of clustering algorithm in data mining (i.e. DM) is explained in this paper. Combined with the characteristics of actual data, a new fuzzy clustering algorithm is adopted. This algorithm does not depend on primary clusters and can determine clusters and their centers. What is more, it can reduce the effect of noises on data and it is suitable for large-scale data. As a result, the further process of data mining is improved a lot. The experiments of actual communications signals show the validity ...
出处
《舰船电子工程》
2008年第4期165-167,共3页
Ship Electronic Engineering
关键词
模糊聚类
聚类半径
预处理
数据挖掘
fuzzy clustering
clustering radius
preprocess
data mining
