A Weighted Fuzzy Rough Sets Model with Hybrid-Attribute Reduction in Granular Computing

您当前的位置：

首页 >

文章列表页 >

A Weighted Fuzzy Rough Sets Model with Hybrid-Attribute Reduction in Granular Computing

更新时间：2025-07-09

- A Weighted Fuzzy Rough Sets Model with Hybrid-Attribute Reduction in Granular Computing
- Vol. 45, Issue 10, Pages: 43-47(2011)
- 作者机构：
  
  郑州大学信息工程学院,郑州,450001
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Online First：10 October 2011，
  
  Published：2011
- 稿件说明：
移动端阅览
A Weighted Fuzzy Rough Sets Model with Hybrid-Attribute Reduction in Granular Computing[J]. 2011, 45(10): 43-47.
DOI：

A Weighted Fuzzy Rough Sets Model with Hybrid-Attribute Reduction in Granular Computing[J]. 2011, 45(10): 43-47. DOI：

摘要

针对权重粗糙集模型不能有效处理非平衡混合数据的问题

对权重论域上的各种类型变量进行分析并建立统一的模糊等价关系

提出混合数据上的权重模糊粗糙集模型

并利用该模型构造出带权模糊等价空间上的混合属性约简算法.混合属性约简算法产生的模糊软划分可以克服权重论域上离散硬划分产生的信息损失.在非平衡混合数据集上进行的实验结果表明

与基于权重粗糙集的算法相比

基于权重模糊粗糙集模型的属性约简算法的平均分类精度提高了11.9%.

Abstract

In order to solve the problem that weighted rough sets model lacks a mechanism to deal with mixed and imbalanced data

a unified fuzzy equivalent relationship for analyzing different types of features in weighted domain is established

and a weighted fuzzy rough sets model is proposed to deal with mixed data. Furthermore

a hybrid attribute-reduction algorithm is constructed based on the weighted fuzzy rough sets model. Compared with the classical crisp partition

the hybrid algorithm can avoid information loss through fuzzy soft partition generated by the model. Experimental results on imbalanced and mixed data sets show that the proposed weighted fuzzy rough sets model can not only select fewer features than weighted rough sets model

but also improve the average classification performance of the reduced attribute set on learning methods by 11.9%.

关键词

Keywords

references

PAWLAK Z, SKOWRON A. Rudiments of rough sets [J]. Information Sciences, 2007, 177(1): 3-27.

王国胤, 于洪, 杨大春. 基于条件信息熵的决策表约简[J]. 计算机学报, 2002, 25(7): 759-766.

WANG Guoyin, YU Hong, YANG Dachun. Decision table reduction based on conditional information entropy [J]. Chinese Journal of Computers, 2002, 25(7): 759-766.

TING K. An instance-weighting method to induce cost-sensitive trees [J]. IEEE Transactions on Knowledge and Data Engineering, 2002, 14(3): 659-665.

谢宏, 程浩忠, 牛东晓. 基于信息熵的粗糙集连续属性离散化算法[J]. 计算机学报, 2005, 28(9): 1570-1574.

XIE Hong, CHENG Haozhong, NIU Dongxiao. Discretization of continuous attributes in rough set theory based on information entropy [J]. Chinese Journal of Computers, 2005, 28(9): 1570-1574.

HU Qinghua, Xie Zongxia, YU Daren. Hybrid attribute reduction based on a novel fuzzy-rough model and information granulation [J]. Pattern Recognition, 2007, 40(12): 3509-3521.

DUBOIS D, PRADE H. Rough fuzzy sets and fuzzy rough sets [J]. International Journal of General Systems, 1990, 17(2): 191-209.

胡清华, 于达仁, 谢宗霞. 基于邻域粒化和粗糙逼近的数值属性约简[J]. 软件学报, 2008, 19(3): 640-649.

HU Qinghua, YU Daren, XIE Zongxia. Numerical attribute reduction based on neighborhood granulation and rough approximation [J]. Chinese Journal of Software, 2008, 19(3): 640-649.

HU Qinghua, LIU Jinfu, YU Daren. Mixed feature selection based on granulation and approximation [J]. Knowledge-Based Systems, 2008, 21(4): 294-304.

XU Changzhi, MIN Fan. Weighted reduction for decision tables [C]∥Proceedings of 3rd International Conference on Fuzzy Systems and Knowledge Discovery. Berlin, Germany: Springer-Verlag, 2006: 246-255.

HU Qinghua, YU Daren, XIE Zongxia, et al. Fuzzy probabilistic approximation spaces and their information measures [J]. IEEE Transactions on Fuzzy Systems, 2006, 14(2): 191-201.

LIU Jinfu, HU Qinghua, YU Daren. A weighted rough set based method developed for class imbalance learning [J]. Information Sciences, 2008, 178(4): 1235-1256.

LIU Yang, FENG Boqin, BAI Guohua. Compact rule learner on weighted fuzzy approximation spaces for class imbalanced and hybrid data [C]∥Proceedings of 6th International Conference on Rough Sets and Current Trends in Computing. Berlin, Gemany: Springer-Verlag, 2008: 262-271.

ZADEH L. Fuzzy sets [J]. Information and Control, 1965, 8(3): 338-353.

LEE H. An optimal algorithm for computing the max-min transitive closure of a fuzzy similarity matrix [J]. Fuzzy Sets and Systems, 2001, 123(1): 129-136.

FRANK A, ASUNCION A. UCI machine learning repository [DB/OL]. [2010-12-22]. http:∥archive.ics.uci.edu/ml.

BREFELD U, GEIBEL P, WYSOTZKI F. Support vector machines with example dependent costs [C]∥Proceedings of the European Conference on Machine Learning. Berlin, Germany, Springer-Verlag, 2003:23-34.

容积粒子滤波算法及其应用. 西安交通大学学报,2011,45(8):13-17.

逆向工程中一种鲁棒的平移对称提取算法. 西安交通大学学报,2011,45(7):70-75.

一种鲁棒的子空间聚类算法. 西安交通大学学报,2011,45(6):13-19.

引入模糊推理与强跟踪滤波技术的变结构多模型估计. 西安交通大学学报,2011,45(6):27-33.

一种采用偏最小二乘回归的情绪调节策略预测模型. 西安交通大学学报,2011,45(6):46-49.

采用任务剖面的复杂可修系统保障性仿真与评价技术研究. 西安交通大学学报,2011,45(4):53-59.

三角Bézier曲面粗加工刀轨生成算法. 西安交通大学学报,2011,45(3):70-74.

广义证据理论中的基本概率指派生成方法. 西安交通大学学报,2011,45(2):34-38.

面向重用的三维CAD模型检索算法. 西安交通大学学报,2011,45(1):74-78.

一种准线性光束平差方法. 西安交通大学学报,2010,44(12):1-4.

广义证据理论的基本框架. 西安交通大学学报,2010,44(12):119-124.

利用特征子空间评价与多分类器融合的高光谱图像分类. 西安交通大学学报,2010,44(8):20-24.

高斯衍生粒子滤波器. 西安交通大学学报,2010,44(6):72-77.

一种多源遥感图像分割的融合新策略. 西安交通大学学报,2010,44(6):88-92.

图像分割的谱聚类集成算法. 西安交通大学学报,2010,44(6):93-98.

应用变量因果序分析的符号有向图建模方法. 西安交通大学学报,2010,44(5):85-90.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Efficient Genetic Reduction Algorithm for Rough Sets

Ant Colony Optimization Approach to Attribute Reduction Problem

An Attribute Reduction Algorithm to Find Learner's Key Characteristics Based on the Discernible Function

Multiple Instance Learning Method Based on Building New Bag Space

An Improved Support Vector Machine Technology for Meta-Information Classification

Related Author

周江卫

冯博琴

刘洋

任志刚 1

冯祖仁 1

柯良军 1

Related Institution

Department of Computer Science and Technology, Xi'an Jiaotong University

Systems Engineering Institute of Xi'an Jiaotong University

State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University

School of Electronics and Information Engineering, Xi'an Jiaotong University

School of Information Science and Technology, Northwest University

⁰