{"title":"基于粗糙集理论的评价技术","authors":"V. Nguyen, Nguyen Thi Ly Sa","doi":"10.1109/ICMLC.2010.5580523","DOIUrl":null,"url":null,"abstract":"Most data mining algorithms usually generate combining large rules, finding useful rules from rules set necessary and important. There have been several techniques proposed to assess the rule as useful measure which is based on rough set theory as the RIM, ERIM measure. On rough set theory has been studied, the article proposed AWERIM measure which is improved from ERIM measure and applied this specific measure to an application of the data mining problem about bank loans.","PeriodicalId":126080,"journal":{"name":"2010 International Conference on Machine Learning and Cybernetics","volume":"252 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating technologies based rough set theory\",\"authors\":\"V. Nguyen, Nguyen Thi Ly Sa\",\"doi\":\"10.1109/ICMLC.2010.5580523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most data mining algorithms usually generate combining large rules, finding useful rules from rules set necessary and important. There have been several techniques proposed to assess the rule as useful measure which is based on rough set theory as the RIM, ERIM measure. On rough set theory has been studied, the article proposed AWERIM measure which is improved from ERIM measure and applied this specific measure to an application of the data mining problem about bank loans.\",\"PeriodicalId\":126080,\"journal\":{\"name\":\"2010 International Conference on Machine Learning and Cybernetics\",\"volume\":\"252 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Machine Learning and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLC.2010.5580523\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2010.5580523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Most data mining algorithms usually generate combining large rules, finding useful rules from rules set necessary and important. There have been several techniques proposed to assess the rule as useful measure which is based on rough set theory as the RIM, ERIM measure. On rough set theory has been studied, the article proposed AWERIM measure which is improved from ERIM measure and applied this specific measure to an application of the data mining problem about bank loans.
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