{"title":"信息特征选择的准浮雕分类方法","authors":"S. Subbotin","doi":"10.1109/STC-CSIT.2018.8526627","DOIUrl":null,"url":null,"abstract":"The feature selection problem for classification is addressed. The modified Relief method is proposed. It selects a subsample from the original sample, computes hashes for instances, used to select and delete redundant instances, compute feature similarity and difference, and updates the feature weights. The experiments to study the proposed method have been carried out. They showed that the proposed method provides a significant acceleration of computations.","PeriodicalId":403793,"journal":{"name":"2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT)","volume":"2007 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Quasi-Relief Method of Informative Features Selection for Classification\",\"authors\":\"S. Subbotin\",\"doi\":\"10.1109/STC-CSIT.2018.8526627\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The feature selection problem for classification is addressed. The modified Relief method is proposed. It selects a subsample from the original sample, computes hashes for instances, used to select and delete redundant instances, compute feature similarity and difference, and updates the feature weights. The experiments to study the proposed method have been carried out. They showed that the proposed method provides a significant acceleration of computations.\",\"PeriodicalId\":403793,\"journal\":{\"name\":\"2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT)\",\"volume\":\"2007 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/STC-CSIT.2018.8526627\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STC-CSIT.2018.8526627","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quasi-Relief Method of Informative Features Selection for Classification
The feature selection problem for classification is addressed. The modified Relief method is proposed. It selects a subsample from the original sample, computes hashes for instances, used to select and delete redundant instances, compute feature similarity and difference, and updates the feature weights. The experiments to study the proposed method have been carried out. They showed that the proposed method provides a significant acceleration of computations.