会议专题

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

2011 Eighth International Conference on Fuzzy System and Knowledge Discovery(第八届模糊系统与知识发现国际会议 FSKD 2011)

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)