Abstract: Clustering analysis is one of primary techniques in the field of data mining.It is an unsupervised mode of pattern recognition.Clustering analysis is a division of data into similarity groups according to given rules.K-means algorithm is a classical clustering algorithm.In the paper K-means’ advantage and weakness is analyzed.A novel clustering algorithm based on artificial fish swarm is proposed then a new mixed clustering algorithm is obtained from the combination of K-means and clustering algorithm which is based on artificial fish swarm.The result of the experiment shows it is a kind of efficient algorithm.

摘要： 聚类分析是数据挖掘的核心技术之一，它是一种无导师监督的模式识别方式。聚类分析就是按照数据间的相似程度，依据特定的准则将数据划分成不同子类。文中通过分析K-平均算法的优缺点，提出了一种基于人工鱼群算法的聚类分析算法，并把它与传统的K-平均算法结合得到一种新的混合聚类算法。仿真实验表明，该算法是有效的，具有聚类速度快、精度高特点。