{"title":"A semi-fuzzy collaborative algorithm for cluster seeking","authors":"Rkia Fajr, Ayoub Arafi, Youssef Safi, A. Bouroumi","doi":"10.1109/SITA.2013.6560795","DOIUrl":null,"url":null,"abstract":"In this paper, we present a semi-fuzzy collaborative algorithm for detecting the optimal number of clusters in a given data set of unlabeled objects. This algorithm is based on a measure of inter-points similarity that allows the detection and creation of clusters, plus a measure of ambiguity that allows collaboration between clusters during their formation. The algorithm also provides a matrix of optimized prototypes representing all the detected clusters. The performance of the proposed method is demonstrated through three examples of test data.","PeriodicalId":145244,"journal":{"name":"2013 8th International Conference on Intelligent Systems: Theories and Applications (SITA)","volume":"31 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th International Conference on Intelligent Systems: Theories and Applications (SITA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITA.2013.6560795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
In this paper, we present a semi-fuzzy collaborative algorithm for detecting the optimal number of clusters in a given data set of unlabeled objects. This algorithm is based on a measure of inter-points similarity that allows the detection and creation of clusters, plus a measure of ambiguity that allows collaboration between clusters during their formation. The algorithm also provides a matrix of optimized prototypes representing all the detected clusters. The performance of the proposed method is demonstrated through three examples of test data.
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