Computer Engineering and Applications ›› 2014, Vol. 50 ›› Issue (2): 152-155.

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Clustering of combining AP with NN model based on time series

LIN Haijuan, CHEN Xiaoyun   

  1. College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China
  • Online:2014-01-15 Published:2014-01-26

基于时间序列的AP-NN混合模型聚类

林海娟,陈晓云   

  1. 福州大学 数学与计算机科学学院,福州 350108

Abstract: Affinity propagation algorithm is a fast and efficient clustering method. However, the stability of clustering results affect its performance of clustering. Thus, a new method combining affinity propagation and nearest neighbor is proposed, this algorithm produces initial clusters through affinity propagation, and then the samples of non-representative cluster clusters to representatives cluster through nearest neighbor clustering. In the time series data set, experimental result shows that AP-NN algorithm can produce effective clustering results and is applied to cluster analysis.

Key words: affinity propagation, time series, cluster analysis, number of clusters

摘要: 仿射传播算法是一种快速有效的聚类方法,但其聚类结果的不稳定性影响了聚类性能。对此,提出基于近邻的仿射传播算法(AP-NN),通过仿射传播算法产生初始簇,并从中选择代表簇对非代表簇的样本进行近邻聚类。在时间序列数据集上的实验结果表明,AP-NN模型算法能够产生较好的聚类结果,适用于聚类分析。

关键词: 仿射传播, 时间序列, 聚类分析, 聚类数