| 基于粗糙集和RBF神经网络的文本自动分类方法 |
| |
| 引用本文： | 白如江.基于粗糙集和RBF神经网络的文本自动分类方法[J].现代图书情报技术,2006,1(6):47-51. |
| |
| 作者姓名： | 白如江 |
| |
| 作者单位： | 山东理工大学图书馆,淄博,255049 |
| |
| 摘 要： | 结合粗糙集的属性约简和RBF神经网络的分类机理，提出一种新的文本分类混合算法。试验结果表明，与朴素贝叶斯、SVM、kNN传统分类方法相比，该方法在保持分类精度的基础上，分类速度有明显提高，体现出较好的稳定性和容错性，尤其适用于特征向量多且难以分类的文本。
|
| 关 键 词： | 粗糙集 神经网络 属性约简 VSM |
| 收稿时间： | 2006-03-21 |
| 修稿时间： | 2006-04-02 |
A Hybrid Classifier Based on the Rough Sets and RBF Neural Networks |
| |
| Bai Rujiang.A Hybrid Classifier Based on the Rough Sets and RBF Neural Networks[J].New Technology of Library and Information Service,2006,1(6):47-51. |
| |
| Authors: | Bai Rujiang |
| |
| Institution: | Library of Shandong University of Technology, Zibo 255049, China |
| |
| 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. |
| |
| Keywords: | VSM |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《现代图书情报技术》浏览原始摘要信息 |
| 点击此处可从《现代图书情报技术》下载免费的PDF全文 |
