| 基于类别选择的改进KNN文本分类 |
| |
| 引用本文： | 刘海峰,张学仁,姚泽清,刘守生.基于类别选择的改进KNN文本分类[J].计算机科学,2009,36(11):213-216. |
| |
| 作者姓名： | 刘海峰 张学仁 姚泽清 刘守生 |
| |
| 作者单位： | 解放军理工大学理学院,南京,210007 |
| |
| 摘 要： | 特征高维性以及算法的泛化能力影响了KNN分类器的分类性能.提出了一种降维条件下基于类别的KNN改进模型,解决了k近邻选择时大类别、高密度样本占优问题.首先使用一种改进的优势率方法进行特征选择,随后使用类别向量对文本类别进行初步判定,最后在压缩后的样本集上使用KNN分类器进行分类.试验结果表明,提出的改进分类模型提高了分类效率.
|
| 关 键 词： | k-最近邻 特征降维 特征选择 文本分类 |
| 收稿时间： | 2008/12/31 0:00:00 |
| 修稿时间： | 3/2/2009 12:00:00 AM |
Improved Sort-based KNN Text Categorization Method |
| |
| LIU Hai-feng,ZHANG Xue-ren,YAO Ze-qing,LIU Shou-sheng.Improved Sort-based KNN Text Categorization Method[J].Computer Science,2009,36(11):213-216. |
| |
| Authors: | LIU Hai-feng ZHANG Xue-ren YAO Ze-qing LIU Shou-sheng |
| |
| Affiliation: | (Institute of Sciences,PLA University of Science and Technology,Nanjing 210007,China) |
| |
| Abstract: | The problem of large feature dimension and the expansibility reduces the KNN function. This paper brougt forward an ameliorative KNN method to solve the problem that big swatch sort with more texts is easy to become the knearest neighbors under the feature reduction condition. Firstly, it used an improved odds radio method to select feature.Secondly, it estimated the possible sorts for the text by using the sort vector. Lastly, it used an improved KNN method in the reduced texts to realize text categorization. The experiment shows that this method has improved the precision. |
| |
| Keywords: | KNN Feature reduction Feature selection Text categorization |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《计算机科学》浏览原始摘要信息 |
|
点击此处可从《计算机科学》下载全文 |
|
