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An Attribute Reduct and Attribute Significance Algorithm of Continuous Domain Decide Table

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成果类型:
期刊论文、会议论文
作者:
Liu Wenjun*
通讯作者:
Liu Wenjun
作者机构:
[Liu Wenjun; Liu, WJ] Changsha Univ Sci & Technol, Dept Math & Comp Sci, Changsha 410076, Hunan, Peoples R China.
通讯机构:
[Liu Wenjun] C
Changsha Univ Sci & Technol, Dept Math & Comp Sci, Changsha 410076, Hunan, Peoples R China.
语种:
英文
关键词:
rough sets;attribute reduc;significance;continuous domain decide table;discernibility matrix
期刊:
ISISE 2008: INTERNATIONAL SYMPOSIUM ON INFORMATION SCIENCE AND ENGINEERING, VOL 2
ISSN:
2160-1283
年:
2008
页码:
293-296
会议名称:
2008 International Symposium on Information Science and Engineering
会议论文集名称:
2008 International Symposium on Information Science and Engineering
会议时间:
December 2008
会议地点:
Shanghai, China
出版者:
IEEE
ISBN:
978-0-7695-3494-7
机构署名:
本校为第一且通讯机构
院系归属:
数学与统计学院
摘要:
Firstly, the author generalizes the indiscernible relation to similarity relation, gives a definition of lambda-discernibility matrix; secondly, an attribute reduct algorithm of decision table with continuous condition attributes is put forward; thirdly, an algorithm of computing significance of each condition attribute is put forward according to the properties of lambda-discernibility matrix; at last, the time complexity of the attribute reduct algorithm is analyzed and the rationality and effectiv...

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