Hierarchical Classification Model Based on MD Feature Selection Method
When dealing with large amounts of textual information, we may require an automatic system to organize them into known taxonomies which are arranged in a hierarchy. This learning task is called hierarchical classification. In such case, usually there are huge numbers of terms. We need apply certain techniques to remove irrelevant and redundant features for saving computation time without losing too much classification accuracy. In this article, we will first propose a new feature selection method called MD. After that a new hierarchical classification method based on MD is proposed and compared with existing methods on a real dataset.
Feature selection Hierarchical classification MD method
Miao Liu Xiaoling Lu Jie Song Xizhi Wu
School of Statistics, Central University of Finance and Economics, Beijing, China Center for Applied Statistics, Renmin University of China, Beijing, China School of Statistics, Renm School of Statistics, Capital University of Economics and Business, Beijing China
国际会议
上海
英文
1862-1865
2011-07-26(万方平台首次上网日期,不代表论文的发表时间)