Attribution reduction algorithm based on discernibility matrix of incomplete decision table

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (24): 103-105.

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

Attribution reduction algorithm based on discernibility matrix of incomplete decision table

SHU Wenhao1，XU Zhangyan1，QIAN Wenbin1，YANG Bingru2

1.School of Computer Science and Information Engineering，Guangxi Normal University，Guilin，Guangxi 541004，China
2.School of Information Engineering，University of Science and Technology Beijing，Beijing 100083，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-08-21 Published:2011-08-21

不完备决策表的差别矩阵属性约简算法

舒文豪1，徐章艳1，钱文彬1，杨炳儒2

1.广西师范大学计算机科学与信息工程学院，广西桂林 541004
2.北京科技大学信息工程学院，北京 100083

Abstract

Abstract: The definition of attribution reduction of discernibility matrix is provided.It is proved that the above definition of attribution reduction is the same as the definition of generalized attribution reduction，the discernibility matrix is compressed.On this condition，in order to compute the attribution reduction of incomplete decision table，a new efficient attribution reduction algorithm based on discernibility matrix is designed，the time complexity of the new algorithm is O(|C|2|U|2).An example is used to illustrate the efficiency of the new algorithm.

Key words: rough set, incomplete decision table, discernibility matrix, attribution reduction, algorithm complexity

摘要： 给出一个差别矩阵的属性约简定义，证明该属性约简的定义与广义决策属性约简的定义是等价的，对差别矩阵进行了有效的压缩。在此基础上，为求出不完备决策表的属性约简，设计了一个基于该差别矩阵的不完备决策表属性约简算法，其时间复杂度为O(|C|2|U|2)，最后用实例说明了该算法的有效性。

关键词: 粗糙集, 不完备决策表, 差别矩阵, 属性约简, 算法复杂度

SHU Wenhao1，XU Zhangyan1，QIAN Wenbin1，YANG Bingru2. Attribution reduction algorithm based on discernibility matrix of incomplete decision table[J]. Computer Engineering and Applications, 2011, 47(24): 103-105.

舒文豪1，徐章艳1，钱文彬1，杨炳儒2. 不完备决策表的差别矩阵属性约简算法[J]. 计算机工程与应用, 2011, 47(24): 103-105.

[1]	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.
[2]	WANG Qingrong, MA Chenkun. Forecast of Emergency Supplies for Case Consumption Reasoning [J]. Computer Engineering and Applications, 2021, 57(22): 281-287.
[3]	LIU Yufeng, SUN Wenxin. Generalized Multi-granulation Quantization Soft Rough Set Model [J]. Computer Engineering and Applications, 2021, 57(12): 137-143.
[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]	ZHANG Bo, JIA Huayu, MA Jun. Estimation of Air Condition for Unmanned Aerial Vehicle Based on RS-GA Neural Network [J]. Computer Engineering and Applications, 2020, 56(4): 209-213.
[6]	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.
[7]	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.
[8]	LUO Gongzhi, MEI Tao. Multi-granulation Decision-Theoretic Rough Set Method Based on Supervisory Mechanism and Its Application [J]. Computer Engineering and Applications, 2020, 56(18): 214-220.
[9]	XIE Xuming, DUAN Longzhen, QIU Taorong, YANG Youfeng. Improved Quantum Search Algorithm and Its Application on Computation of Core [J]. Computer Engineering and Applications, 2020, 56(14): 57-61.
[10]	LI Xu, RONG Zijing, REN Yan. Attribute Reduction on Weighted Decision Table [J]. Computer Engineering and Applications, 2020, 56(12): 54-59.
[11]	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.
[12]	REN Jun1, TANG Qiwen1, XU Yi2, HU Shanzhong2. Research on Multi Granularity Rough Set for University Students’ Poverty Support Evaluation [J]. Computer Engineering and Applications, 2019, 55(7): 82-86.
[13]	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.
[14]	QI Meilan, LI Xiaonan. Matroidal Structure Based on Set-Valued Mapping and Its Relationship with Covering Rough Sets [J]. Computer Engineering and Applications, 2019, 55(6): 50-56.
[15]	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.

Attribution reduction algorithm based on discernibility matrix of incomplete decision table

不完备决策表的差别矩阵属性约简算法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics