关键词: 仿射传播, 时间序列, 聚类分析, 聚类数

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