{"title":"基于粗糙集的改进属性约简算法","authors":"X. Yang, Jiancheng Wan, Ling Zhang","doi":"10.1109/SNPD.2007.181","DOIUrl":null,"url":null,"abstract":"An improved heuristic attribute reduction algorithm based on the attribute frequency is presented. After analyzing many other attribute reduction algorithms, we utilize the discernibility matrix and the appeared attribute frequencies to determine each attribute's significance, based on the principle of maximum attribute frequency, we achieved the reduction of the information system. An illustrative example demonstrate the algorithm's effectiveness and validity.","PeriodicalId":197058,"journal":{"name":"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"An Improved Attribute Reduction Algorithm Based on Rough Set\",\"authors\":\"X. Yang, Jiancheng Wan, Ling Zhang\",\"doi\":\"10.1109/SNPD.2007.181\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An improved heuristic attribute reduction algorithm based on the attribute frequency is presented. After analyzing many other attribute reduction algorithms, we utilize the discernibility matrix and the appeared attribute frequencies to determine each attribute's significance, based on the principle of maximum attribute frequency, we achieved the reduction of the information system. An illustrative example demonstrate the algorithm's effectiveness and validity.\",\"PeriodicalId\":197058,\"journal\":{\"name\":\"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SNPD.2007.181\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2007.181","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Attribute Reduction Algorithm Based on Rough Set
An improved heuristic attribute reduction algorithm based on the attribute frequency is presented. After analyzing many other attribute reduction algorithms, we utilize the discernibility matrix and the appeared attribute frequencies to determine each attribute's significance, based on the principle of maximum attribute frequency, we achieved the reduction of the information system. An illustrative example demonstrate the algorithm's effectiveness and validity.