Abstract: The paper studies feature selection in text categorization learning. It focuses on dimensionality reduction. Because high dimensionality feature sets are not all important and available in categorization learning. In the end some categorization methods and characteristics were introduced.

摘要： 研究了文本分类学习中的特征选取，主要集中在大幅度降维的评估函数，因为高维的特征集对分类学习未必全是重要的和有用的。还介绍了分类的一些方法及其特点。

关键词: 文本分类, 特征选取, 降维

CLC Number: 

• TP181