{"title":"Binary classification with noise via fuzzy weighted least squares twin support vector machine","authors":"Juntao Li, Yimin Cao, Yadi Wang, Xiaoxia Mu, Liuyuan Chen, Huimin Xiao","doi":"10.1109/CCDC.2015.7162214","DOIUrl":null,"url":null,"abstract":"A new weighted least squares twin support vector machine for binary classification with noise is proposed in this paper. By using the distances from the sample points to their class center, fuzzy weights are constructed. The fuzzy weighted least squares twin support vector machine is presented by following the fuzzy weighted mechanism, thus reducing the influence of the noise. The simulation results on three UCI data and two-moons data demonstrate the effectiveness of the proposed method.","PeriodicalId":273292,"journal":{"name":"The 27th Chinese Control and Decision Conference (2015 CCDC)","volume":"518 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 27th Chinese Control and Decision Conference (2015 CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2015.7162214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A new weighted least squares twin support vector machine for binary classification with noise is proposed in this paper. By using the distances from the sample points to their class center, fuzzy weights are constructed. The fuzzy weighted least squares twin support vector machine is presented by following the fuzzy weighted mechanism, thus reducing the influence of the noise. The simulation results on three UCI data and two-moons data demonstrate the effectiveness of the proposed method.
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