{"title":"基于知识粒度的快速属性约简算法","authors":"Zhangyan Xu, Wei Zhang, Xiaoyu Wang, Xiaoyu Li","doi":"10.1109/FSKD.2012.6233802","DOIUrl":null,"url":null,"abstract":"The research of knowledge granularity has been a hotspot at home and abroad. In incomplete information systems of the rough set, we give a formula, which calculates the attribute frequency directly without acquiring the discernibility matrix. Then applying it to the field of knowledge granularity, we give a quick calculation of the attribute reduction algorithm, which of the time complexity is O(|C|2 |U |) in the worst case. The example result shows that the algorithm is correct and efficient.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A quick attribute reduction algorithm based on knowledge granularity\",\"authors\":\"Zhangyan Xu, Wei Zhang, Xiaoyu Wang, Xiaoyu Li\",\"doi\":\"10.1109/FSKD.2012.6233802\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The research of knowledge granularity has been a hotspot at home and abroad. In incomplete information systems of the rough set, we give a formula, which calculates the attribute frequency directly without acquiring the discernibility matrix. Then applying it to the field of knowledge granularity, we give a quick calculation of the attribute reduction algorithm, which of the time complexity is O(|C|2 |U |) in the worst case. The example result shows that the algorithm is correct and efficient.\",\"PeriodicalId\":337941,\"journal\":{\"name\":\"International Conference on Fuzzy Systems and Knowledge Discovery\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Fuzzy Systems and Knowledge Discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FSKD.2012.6233802\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Fuzzy Systems and Knowledge Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FSKD.2012.6233802","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A quick attribute reduction algorithm based on knowledge granularity
The research of knowledge granularity has been a hotspot at home and abroad. In incomplete information systems of the rough set, we give a formula, which calculates the attribute frequency directly without acquiring the discernibility matrix. Then applying it to the field of knowledge granularity, we give a quick calculation of the attribute reduction algorithm, which of the time complexity is O(|C|2 |U |) in the worst case. The example result shows that the algorithm is correct and efficient.
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