作者: Yu Wang , Zheng-Ou Wang
DOI: 10.1109/ICMLC.2005.1527296
关键词: Statistic 、 Fuzzy decision tree 、 Data mining 、 Pearson's chi-squared test 、 Mathematics 、 Vector space 、 Machine learning 、 Text mining 、 Artificial intelligence 、 Decision tree 、 Fuzzy set 、 Categorization
摘要: In this paper, a new method for text categorization rule extraction based on fuzzy decision tree is presented. An improved chi-square statistic adopted. The reduces features of in terms the statistic, and so largely dimensions vector space. And then, construction membership functions presented, which time data fuzzification increase accuracy consequently. Finally, applied to categorization. Both understandable rules better can be acquired.