Matrix Description for Attribute Reduction   Based on Skowron Discernibility Matrix

doi:10.3969/j.issn.1000-3428.2010.17.019

Computer Engineering ›› 2010, Vol. 36 ›› Issue (17): 54-56. doi: 10.3969/j.issn.1000-3428.2010.17.019

• Networks and Communications • Previous Articles Next Articles

Matrix Description for Attribute Reduction Based on Skowron Discernibility Matrix

MENG Ren1, XU Zhang-yan2,3, YANG Bing-ru3

(1. Finance Office, Guangxi Normal University, Guilin 541004; 2. Department of Computer, Guangxi Normal University, Guilin 541004; 3. School of Information Engineering, University of Science and Technology Beijing, Beijng 100083)

Online:2010-09-05 Published:2010-09-02

基于Skowron差别矩阵属性约简的矩阵表示

蒙韧1，徐章艳2,3，杨炳儒3

(1. 广西师范大学财务处，桂林 541004；2. 广西师范大学计算机系，桂林 541004；3. 北京科技大学信息工程学院，北京 100083)

作者简介:蒙韧(1973－)，男，工程师，主研方向：粗糙集理论及应用，数据挖掘；徐章艳，副教授、博士；杨炳儒，教授、博士生导师
基金资助:
国家自然科学基金资助项目(69063008)；广西教育厅基金资助项目( 200807MS015)；广西师范大学博士基金资助项目

Abstract

Abstract: At present, there are no researcheres using matrix method to design attribute reduction algorithm based on Skowron discernibility matrix. Aiming at this problem, in this paper, a new matrix is proposed, and an attribute reduction based on the new matrix is provided. It is proved that the new attribute reduction definition is the same as that based on Skowron discernibility matrix. It uses the matrix of attribute to define the significance of attribute, and designs a new attribute reduction algorithm based on Skowron discernibility matrix. Example proves the validity of the algorithm.

Key words: Skowron discernibility matrix, matrix, attribute reduction

摘要： 针对目前基于Skowron差别矩阵的属性约简中缺少矩阵表示的问题，定义一种新的矩阵，并给出基于新矩阵的属性约简定义，证明该定义与基于Skowron差别矩阵的属性约简等价。以矩阵为基础，定义属性的重要性，设计一个基于Skowron差别矩阵的属性约简算法，实例证明了算法的有效性。

关键词: Skowron差别矩阵, 矩阵, 属性约简

CLC Number:

TP311

MENG Ren, XU Zhang-Yan, YANG Bing-Ru. Matrix Description for Attribute Reduction Based on Skowron Discernibility Matrix[J]. Computer Engineering, 2010, 36(17): 54-56.

蒙韧, 徐章艳, 杨炳儒. 基于Skowron差别矩阵属性约简的矩阵表示[J]. 计算机工程, 2010, 36(17): 54-56.

/ / Recommend / Download Citations

URL: http://www.ecice06.com/EN/10.3969/j.issn.1000-3428.2010.17.019

http://www.ecice06.com/EN/Y2010/V36/I17/54

[1]	Junhang CHEN, Zuyuan YANG, Mingyang LIU, Lingjiang LI. Generalized Separable Nonnegative Matrix Factorization Algorithm Based on Orthogonal Constraints [J]. Computer Engineering, 2023, 49(8): 46-53.
[2]	Bo LIU, Xiaoxia LI, Jiamin QIN, Yingyue ZHOU. Segmentation for Esophageal Precancerous Lesions Region Using Globally Correlated Block-Level Self-Attention [J]. Computer Engineering, 2023, 49(7): 313-320.
[3]	Ziwei HUI, Kun HE, Ben FENG, Yao SU. Image Quality Assessment Based on Visual Characteristics [J]. Computer Engineering, 2023, 49(7): 189-195.
[4]	XU Yi, HOU Di. Fast Calculation Algorithm of Approximations in Rough Sets Based on Matrices [J]. Computer Engineering, 2023, 49(5): 22-28.
[5]	HU Huiqi, ZHANG Weiqiang, XU Chen. Discriminant Enhanced Sparse Subspace Clustering [J]. Computer Engineering, 2023, 49(2): 98-104.
[6]	LI Linke, KANG Zhao, LONG Bo. Riemannian Manifold Based Multi-View Spectral Clustering Algorithm [J]. Computer Engineering, 2023, 49(1): 113-120,129.
[7]	LIU Hang, YIN Xin, CHEN Jie, LUO Heng. Multi-Dimensional Time-Series Prediction Based on Hybrid Network Models [J]. Computer Engineering, 2023, 49(1): 121-129.
[8]	WANG Fuping, YU Juntao, ZHANG Qieshi. Color Edge Detection Based on Adaptive Directional Derivative Filter [J]. Computer Engineering, 2022, 48(9): 204-212.
[9]	QIU Honghui, LIU Hailin, CHEN Lei. Multi-Objective Multi-Tasking Optimization Algorithm Based on Adjustment of Covariance Matrix [J]. Computer Engineering, 2022, 48(8): 306-312.
[10]	HE Na, MA Yingcang. Multi-View Fuzzy Clustering Algorithm Fused with KL Information [J]. Computer Engineering, 2022, 48(7): 114-121,150.
[11]	WANG Xiyang, CHEN Jilin, LI Meng, LIU Shouwen. Static Scheduling Algorithm for Solving Sparse Matrixes on FPGA Architecture [J]. Computer Engineering, 2022, 48(7): 199-205,213.
[12]	FAN Linge, WU Xinrong, TONG Wei, ZENG Weijun. Feature Selection Method for Incomplete Data Sets Based on Probability Matrix Decomposition [J]. Computer Engineering, 2022, 48(6): 57-64.
[13]	RAN Yi, WANG Runnian, PAN Hongwei, YU Haimeng, YUAN Peisen. Factorization Machine Model for Power Outage Classification Prediction [J]. Computer Engineering, 2022, 48(5): 98-103,111.
[14]	ZHU Liming, DING Xiaobo, GONG Guoqiang. Privacy Protection Method in Continuous Publishing of Graph Data [J]. Computer Engineering, 2022, 48(5): 154-161.
[15]	CAO Zhongxiao, FENG Yangde, WANG Jue, MIN Weixiao, YAO Tiechui, GAO Yue, WANG Lihua, GAO Fuhai. Computing Performance Prediction Model for Sparse Matrix Vector Multiplication Based on Deep Learning [J]. Computer Engineering, 2022, 48(2): 86-91.

Please choose a citation manager

Content to export

Matrix Description for Attribute Reduction Based on Skowron Discernibility Matrix

基于Skowron差别矩阵属性约简的矩阵表示

PDF

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments

模态框（Modal）标题

Please choose a citation manager

Content to export

Matrix Description for Attribute Reduction Based on Skowron Discernibility Matrix

基于Skowron差别矩阵属性约简的矩阵表示

PDF

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments