Ambiguity measure-based feature selection for text categorization

Feature selection is one of methods that reduce the size of the number of features in text categorization. In this paper, we proposed a feature selection method, which filtered some features that only rarely occur in one category and do not occur in other categories from the feature subset generated by ambiguity measure method. The experiments show that the proposed method can improve the performance in the context of special classifier and text corpus.