{"title":"Research and experiment on Affinity Propagation clustering algorithm","authors":"Huan Zhang, Kun Song","doi":"10.1109/MACE.2011.5988401","DOIUrl":null,"url":null,"abstract":"This paper introduces Affinity Propagation (AP) clustering algorithm, which is intensively researched by some scholars owing to its advantage of fast speed and no need of setting the initial clusters manually. Mainly analyzed the characteristics of Affinity Propagation clustering algorithm at first, and then compared several principle similarity calculating methods based on Euclidean distance and Mahalanobis distance and etc. Experiment on AP clustering algorithm were done with the parts of the UCI data sets, thus the effectiveness of this algorithm was verified. Finally, the experimental results were analyzed in general.","PeriodicalId":6400,"journal":{"name":"2011 Second International Conference on Mechanic Automation and Control Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Second International Conference on Mechanic Automation and Control Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MACE.2011.5988401","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper introduces Affinity Propagation (AP) clustering algorithm, which is intensively researched by some scholars owing to its advantage of fast speed and no need of setting the initial clusters manually. Mainly analyzed the characteristics of Affinity Propagation clustering algorithm at first, and then compared several principle similarity calculating methods based on Euclidean distance and Mahalanobis distance and etc. Experiment on AP clustering algorithm were done with the parts of the UCI data sets, thus the effectiveness of this algorithm was verified. Finally, the experimental results were analyzed in general.