关键词: 文本分类;降维;评价函数

Abstract:

Reducing the high dimension of feature vectors is an essential part of text categorization. After studying current dimension reduction technique and analyzing some normal methods of feature selection, a new approach, named CDF, in feature selection was proposed by comprehensively taking concentration among classes, distribution in class and average frequency in class into account. Experiment takes K-nearest neighbor(KNN) as the evaluating classifier. Experiment results prove that CDF approach is simple and effective, and get a better performance than conventional feature selection methods in dimension reduction.