关键词: 特征提取, 特征分布, 类间集中度, 类内离散度, 文档-最少出现文档频率（TF-LDF）

Abstract: Conventional methods of text feature extraction are inadequate at distribution quantification, which to a large extent affects the efficiency of classification. Aiming at this problem, a scheme of Least Document Frequency（LDF） is proposed, which can quantify the concentration and dispersion among feature classes through LDF, thus can reflect the characteristics of the distribution more accurately. Through experiments, TF-LDF algorithm can acquire a better result.

Key words: feature extraction, feature distribution, concentration among classes, dispersion within class, Term Frequency-Least Document Frequency（TF-LDF）