{"title":"连续信息系统中一种新的属性约简算法","authors":"Yuejin Lv, Hong-yun Zhang, Fen Quan, Zhi-cheng Chen","doi":"10.1109/CIS.2007.191","DOIUrl":null,"url":null,"abstract":"This paper puts forward a new method of discretizing continuous attributes. Compared with the traditional approach, the method, proposed in this paper, can make the number of the obtained classes be more moderate, as well as the lost information be fewer. And then a simple attribute reduction algorithm is developed in continuous information systems. Finally, a real example is used to illustrate its feasibility and effectiveness, respectively.","PeriodicalId":127238,"journal":{"name":"2007 International Conference on Computational Intelligence and Security (CIS 2007)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A New Attribute Reduction Algorithm in Continuous Information Systems\",\"authors\":\"Yuejin Lv, Hong-yun Zhang, Fen Quan, Zhi-cheng Chen\",\"doi\":\"10.1109/CIS.2007.191\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper puts forward a new method of discretizing continuous attributes. Compared with the traditional approach, the method, proposed in this paper, can make the number of the obtained classes be more moderate, as well as the lost information be fewer. And then a simple attribute reduction algorithm is developed in continuous information systems. Finally, a real example is used to illustrate its feasibility and effectiveness, respectively.\",\"PeriodicalId\":127238,\"journal\":{\"name\":\"2007 International Conference on Computational Intelligence and Security (CIS 2007)\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Computational Intelligence and Security (CIS 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS.2007.191\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Computational Intelligence and Security (CIS 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2007.191","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Attribute Reduction Algorithm in Continuous Information Systems
This paper puts forward a new method of discretizing continuous attributes. Compared with the traditional approach, the method, proposed in this paper, can make the number of the obtained classes be more moderate, as well as the lost information be fewer. And then a simple attribute reduction algorithm is developed in continuous information systems. Finally, a real example is used to illustrate its feasibility and effectiveness, respectively.
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