微型机与应用Issue(21)：81-84,4.
粗糙集属性约简在文本分类中的性能研究
Study on performance of rough set attribute reduction in text categorization
赵靖 1皮建勇2
作者信息
- 1. 贵州大学 计算机科学与技术学院，贵州 贵阳 550025
- 2. 贵州大学 云计算与物联网研究中心，贵州 贵阳 550025
- 折叠
摘要
Abstract
Feature space dimension can reach tens of thousands in text auto classification. Dimension is still large after feature selection using the method of information measure such as document frequency , information gain and mutual information. Reducing the threshold or the minimum number of selected features may result in classification performance degradation. The solution for this situation is implemented with the attribute reduction again based on rough set theory. Experiment indicates that this method can effectively reduce the feature dimension, as well as ensure the performance of classification.关键词
文本分类/粗糙集/属性约简Key words
text classfication/rough set/attribute reduction分类
计算机与自动化引用本文复制引用
赵靖,皮建勇..粗糙集属性约简在文本分类中的性能研究[J].微型机与应用,2015,(21):81-84,4.
