Text categorization rule extraction based on fuzzy decision tree

作者: Yu Wang , Zheng-Ou Wang

DOI: 10.1109/ICMLC.2005.1527296

关键词: StatisticFuzzy decision treeData miningPearson's chi-squared testMathematicsVector spaceMachine learningText miningArtificial intelligenceDecision treeFuzzy setCategorization

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.

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