Please wait a minute...
New Technology of Library and Information Service  2006, Vol. 1 Issue (6): 47-51    DOI: 10.11925/infotech.1003-3513.2006.06.12
Current Issue | Archive | Adv Search |
A Hybrid Classifier Based on the Rough Sets and RBF Neural Networks
Bai Rujiang
(Library of Shandong University of Technology, Zibo 255049,China)
Download: PDF (0 KB)  
Export: BibTeX | EndNote (RIS)      
Abstract  

This paper presentes a new hybrid classifier based on the combination of rough set theory and RBF neural network. Experimental results show that the algorithm Rough-RBF is effective for the texts classification, and has the better performance in classification precision, stability and fault-tolerance comparing with the traditional classification methods, Bayesian classifiers SVM and kNN, especially for the complex classification problems with many feature vectors.

Key wordsText classification      Rough-sets      Neural network      Attribute reduction      VSM     
Received: 21 March 2006      Published: 25 June 2006
ZTFLH: 

TP391

 
Corresponding Authors: Bai Rujiang     E-mail: brj@sdut.edu.cn
About author:: Bai Rujiang

Cite this article:

Bai Rujiang . A Hybrid Classifier Based on the Rough Sets and RBF Neural Networks. New Technology of Library and Information Service, 2006, 1(6): 47-51.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2006.06.12     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2006/V1/I6/47

1施洁斌.基于概率神经网络的文本自动分类研究.情报学报,2004 ,23(2) :147-151
2Pawalk Z. Rough sets . International Journal of Computer and Information Science ,1982 ,11(5) : 341-356
3Pawalk Z. Rough sets : theoretical aspects of reasoning about data. Norwell: Kluwer Academic Publishers ,1991
4Skowron A. Rough Sets and Boolean Reasoning. New York : PhysicalVerlag ,2001. 95-124
5Ziako W. Rough sets : trends , challenges , and prospects. Rough Sets and Current Trends in Computing .Berlin : Springer Verlag ,2001. 1-7
6赵群,保铮. 径向基函数神经网络的分类机理. 通信学报,1996 ,17 (2) :31234
7李斗,李弼程.一种神经网络文本分类器的设计与实现.计算机工程与应用,2005(17):107-109
8郝占刚,王正欧.基于潜在语义索引和遗传算法的文本特征提取方法.情报科学,2006(1):104-107
9Ahn B S , Cho S S , Kim C. The integrated methodology of rough set theory and artificial neural network for business failure prediction. Expert Systems with Applications , 2000 ,18 (2) :65 - 74
10张建宝,慈林林,赵宗涛. RBF 网络分类器的实现及应用. 计算机工程与科学,2001 ,23 (6) :18-22
11David Hand著,张银奎译.数据挖掘原理.北京:机械工业出版社,2003

[1] Qiu Erli,He Hongwei,Yi Chengqi,Li Huiying. Research on Public Policy Support Based on Character-level CNN Technology[J]. 数据分析与知识发现, 2020, 4(7): 28-37.
[2] Wang Sidi,Hu Guangwei,Yang Siyu,Shi Yun. Automatic Transferring Government Website E-Mails Based on Text Classification[J]. 数据分析与知识发现, 2020, 4(6): 51-59.
[3] Liu Weijiang,Wei Hai,Yun Tianhe. Evaluation Model for Customer Credits Based on Convolutional Neural Network[J]. 数据分析与知识发现, 2020, 4(6): 80-90.
[4] Wang Mo,Cui Yunpeng,Chen Li,Li Huan. A Deep Learning-based Method of Argumentative Zoning for Research Articles[J]. 数据分析与知识发现, 2020, 4(6): 60-68.
[5] Yan Chun,Liu Lu. Classifying Non-life Insurance Customers Based on Improved SOM and RFM Models[J]. 数据分析与知识发现, 2020, 4(4): 83-90.
[6] Su Chuandong,Huang Xiaoxi,Wang Rongbo,Chen Zhiqun,Mao Junyu,Zhu Jiaying,Pan Yuhao. Identifying Chinese / English Metaphors with Word Embedding and Recurrent Neural Network[J]. 数据分析与知识发现, 2020, 4(4): 91-99.
[7] Xu Yuemei,Liu Yunwen,Cai Lianqiao. Predicitng Retweets of Government Microblogs with Deep-combined Features[J]. 数据分析与知识发现, 2020, 4(2/3): 18-28.
[8] Xiang Fei,Xie Yaotan. Recognition Model of Patient Reviews Based on Mixed Sampling and Transfer Learning[J]. 数据分析与知识发现, 2020, 4(2/3): 39-47.
[9] Ni Weijian,Guo Haoyu,Liu Tong,Zeng Qingtian. Online Product Recommendation Based on Multi-Head Self-Attention Neural Networks[J]. 数据分析与知识发现, 2020, 4(2/3): 68-77.
[10] Bengong Yu,Yumeng Cao,Yangnan Chen,Ying Yang. Classification of Short Texts Based on nLD-SVM-RF Model[J]. 数据分析与知识发现, 2020, 4(1): 111-120.
[11] Weimin Nie,Yongzhou Chen,Jing Ma. A Text Vector Representation Model Merging Multi-Granularity Information[J]. 数据分析与知识发现, 2019, 3(9): 45-52.
[12] Yunfei Shao,Dongsu Liu. Classifying Short-texts with Class Feature Extension[J]. 数据分析与知识发现, 2019, 3(9): 60-67.
[13] Heran Qin,Liu Liu,Bin Li,Dongbo Wang. Automatic Classification of Ancient Classics with Entity Features[J]. 数据分析与知识发现, 2019, 3(9): 68-76.
[14] Guo Chen,Tianxiang Xu. Sentence Function Recognition Based on Active Learning[J]. 数据分析与知识发现, 2019, 3(8): 53-61.
[15] Zhenyu He,Xiangxiang Dong,Qinghua Zhu. Classifying Baidu Encyclopedia Entries with User Behaviors[J]. 数据分析与知识发现, 2019, 3(6): 117-122.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn