CAJ | 학술논문

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。
방사전파산법시일충쾌속유효적취류방법，단기취류결과적불은정성영향료취류성능。대차，제출기우근린적방사전파산법（AP-NN），통과방사전파산법산생초시족，병종중선택대표족대비대표족적양본진행근린취류。재시간서렬수거집상적실험결과표명，AP-NN모형산법능구산생교호적취류결과，괄용우취류분석。
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.