{"title":"基于属性显著性评价的数据约简方法","authors":"Chao-bo He, Qimai Chen","doi":"10.1109/IWISA.2010.5473715","DOIUrl":null,"url":null,"abstract":"According to the problem of attribute subset selection,the paper put forward a method based on evaluation of attribute significance.Based on the rough set theories the method first defined the calculation formula of attribute significance and designed the corresponding solution algorithm,whose running time complexity decreased about |U|2 orders of magnitude comparing with the similar algorithm on the same test dataset with |U| rescords.The result of application example shows that this method can reserve the condition attributes,which are important for decision attributes,and also can perform the data reduction operation effectively.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Method for Data Reduction Based on Evaluation of Attribute Significance\",\"authors\":\"Chao-bo He, Qimai Chen\",\"doi\":\"10.1109/IWISA.2010.5473715\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"According to the problem of attribute subset selection,the paper put forward a method based on evaluation of attribute significance.Based on the rough set theories the method first defined the calculation formula of attribute significance and designed the corresponding solution algorithm,whose running time complexity decreased about |U|2 orders of magnitude comparing with the similar algorithm on the same test dataset with |U| rescords.The result of application example shows that this method can reserve the condition attributes,which are important for decision attributes,and also can perform the data reduction operation effectively.\",\"PeriodicalId\":298764,\"journal\":{\"name\":\"2010 2nd International Workshop on Intelligent Systems and Applications\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 2nd International Workshop on Intelligent Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWISA.2010.5473715\",\"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 2nd International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWISA.2010.5473715","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Method for Data Reduction Based on Evaluation of Attribute Significance
According to the problem of attribute subset selection,the paper put forward a method based on evaluation of attribute significance.Based on the rough set theories the method first defined the calculation formula of attribute significance and designed the corresponding solution algorithm,whose running time complexity decreased about |U|2 orders of magnitude comparing with the similar algorithm on the same test dataset with |U| rescords.The result of application example shows that this method can reserve the condition attributes,which are important for decision attributes,and also can perform the data reduction operation effectively.
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