{"title":"A New Approach to Classification with the Least Number of Features","authors":"Sascha Klement, T. Martinetz","doi":"10.1109/ICMLA.2010.28","DOIUrl":null,"url":null,"abstract":"Recently, the so-called Support Feature Machine (SFM) was proposed as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separating hyper plane. We propose an extension for linearly non-separable datasets that allows a direct trade-off between the number of misclassified data points and the number of dimensions. Results on toy examples as well as real-world datasets demonstrate that this method is able to identify relevant features very effectively.","PeriodicalId":336514,"journal":{"name":"2010 Ninth International Conference on Machine Learning and Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Ninth International Conference on Machine Learning and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLA.2010.28","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
Recently, the so-called Support Feature Machine (SFM) was proposed as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separating hyper plane. We propose an extension for linearly non-separable datasets that allows a direct trade-off between the number of misclassified data points and the number of dimensions. Results on toy examples as well as real-world datasets demonstrate that this method is able to identify relevant features very effectively.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
