Text feature selection method can affect the effect of text classification directly.
特征选择方法的好坏直接影响文本分类的效果。
Text feature selection is a process of recognizing and deleting redundant information and enhancing training documents cluster quality.
文本特征选择是最大程度地识别和去除冗余信息，提高训练数据集质量的过程。
The author gains insights from attribute reduction based on discernability matrix and proposes a few rough-set based text feature selection algorithms, i. e. , DB1, DB2 and LDB.
作者从基于分辨矩阵的粗糙集属性约简中受到启发，提出了一系列基于粗集理论的文本特征选择算法，即DB1、DB2、LDB。
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