Continuous attribute reduction based on fuzzy rough dependence degree

doi:10.3778/j.issn.1002-8331.2010.17.038

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (17): 136-138.DOI: 10.3778/j.issn.1002-8331.2010.17.038

• 数据库、信号与信息处理 • Previous Articles Next Articles

Continuous attribute reduction based on fuzzy rough dependence degree

ZHAI Xing-long，LI Xu-wu

Department of Computer Engineering，Missile Institute，Air Force Engineering University，Sanyuan，Shaanxi 713800，China

Received:2009-12-24 Revised:2010-03-29 Online:2010-06-11 Published:2010-06-11
Contact: ZHAI Xing-long

基于模糊粗糙依赖度的连续值属性约简

翟兴隆，李续武

空军工程大学导弹学院计算机工程系，陕西三原 713800

通讯作者: 翟兴隆

Abstract

Abstract: As to the problem of information loss in the process of discretization，a method of attribute reduction based on the fuzzy rough sets theory is described.A model of rough sets under fuzzy equivalent relations is systematically investigated.The definitions of positive field，dependence degree are given.And an attribute reduction algorithm based on fuzzy rough dependence degree is particularly analyzed，which is more efficient than the traditional methods.Experiments show the feasibility of the application of the algorithm.

Key words: fuzzy rough sets, dependence degree, continuous features, attribute reduction

摘要： 针对传统的离散化技术所造成的信息丢失问题，提出了利用模糊粗糙集理论来进行属性约简的方法。描述了模糊等价关系下的粗糙集模型，定义了正域、依赖度等概念，提出了基于模糊粗糙依赖度的属性约简算法，该方法比传统属性约简方法具有更好的时间复杂性，并用实例证明了该算法的可行性。

关键词: 模糊粗糙集, 依赖度, 连续值, 属性约简

CLC Number:

TP182

ZHAI Xing-long，LI Xu-wu. Continuous attribute reduction based on fuzzy rough dependence degree[J]. Computer Engineering and Applications, 2010, 46(17): 136-138.

翟兴隆，李续武. 基于模糊粗糙依赖度的连续值属性约简[J]. 计算机工程与应用, 2010, 46(17): 136-138.

[1]	DAI Qi, LI Min, LIU Yang, LI Lihong. Fast Attribute Reduction Algorithm Based on Fuzzy Hierarchical Quotient Space [J]. Computer Engineering and Applications, 2021, 57(4): 55-60.
[2]	GAO Tianyu, WANG Qingrong, YANG Lei. Data Mining Model Based on Attribute Dependability Enhancement of Rough Set [J]. Computer Engineering and Applications, 2021, 57(3): 87-93.
[3]	ZHANG Chengling, LI Jinjin, LIN Yidong. Attribute Reduction in Formal Contexts Based on OE-Concept Lattices [J]. Computer Engineering and Applications, 2021, 57(15): 82-89.
[4]	LIU Guizhi. Incremental Attribute Reduction of Incomplete Hybrid Data Based on Dimension Change [J]. Computer Engineering and Applications, 2021, 57(12): 161-169.
[5]	MOU En, ZHANG Xianyong, YAO Yuesong, DENG Qie. Class-Specific Attribute Reduct and Its Heuristic Algorithm of Neighborhood Approximation Condition-Entropy [J]. Computer Engineering and Applications, 2020, 56(24): 175-180.
[6]	ZHANG Jianhua, LI Fangfang, YANG Lan. Research on Matching Supply and Demand of Case Knowledge Based on PFS and RS [J]. Computer Engineering and Applications, 2020, 56(23): 139-145.
[7]	LI Xu, RONG Zijing, REN Yan. Attribute Reduction on Weighted Decision Table [J]. Computer Engineering and Applications, 2020, 56(12): 54-59.
[8]	CHEN Panpan, LIN Menglei. Attributes Reduction of Single Valued Neutrosophic Decision Information System Based on Inclusion Degree [J]. Computer Engineering and Applications, 2020, 56(12): 175-181.
[9]	WU Yangyang, TANG Jianguo. Research Progress of Attribute Reduction Based on Rough Set in Context of Big Data [J]. Computer Engineering and Applications, 2019, 55(6): 31-38.
[10]	YANG Zhen, GENG Xiuli. Research on Mining Association Rules Based on Multi-Granularity Attribute Reduction [J]. Computer Engineering and Applications, 2019, 55(6): 133-139.
[11]	LI Yun, MA Yinghong. Node Importance Rank by Attribute Reduction Set Evaluation [J]. Computer Engineering and Applications, 2019, 55(5): 149-158.
[12]	REN Xiaoxia1, XUE Fan2，3. Heuristic attribute reduction algorithm based on fuzzy neighborhood rough set [J]. Computer Engineering and Applications, 2018, 54(9): 47-53.
[13]	WANG Changbao1, YANG Xibei1，2, DOU Huili1, CHEN Xiangjian1, WANG Pingxin3. Research on local attribute reduction approach via neighborhood decision error rate [J]. Computer Engineering and Applications, 2018, 54(6): 95-99.
[14]	CHEN Jian, ZHANG Xiaohong. Approximately data detecting method based on fusion of information entropy and fuzzy integrated evaluation [J]. Computer Engineering and Applications, 2018, 54(24): 57-60.
[15]	ZHENG Na, WANG Jiayang. Evidence characteristics and attribute reduction of incomplete ordered information system [J]. Computer Engineering and Applications, 2018, 54(21): 43-47.

Continuous attribute reduction based on fuzzy rough dependence degree

基于模糊粗糙依赖度的连续值属性约简

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics