关键词: 文本分类, 信息增益, 类词频, 倒逆转文档频率, 特征选择

Abstract: Feature selection is the key step of Uyghur text classification, which causes direct effect on the categorization results. To improve the effect of traditional information gain algorithm on the Uyghur feature selection, a new information gain feature selection method is proposed on the basis of deep?analysis of Uyghur text feature. This method combines with word frequency in class, characteristics of the distribution coefficient and inverse document frequency, thus traditional information gain is modified. Furthermore, it introduces an alternative features of distribution coefficient to balance the selected number between the classes. Finally, ?experimental verification?is conducted on Uyghur text dataset. The results show that modified information gain algorithm has greatly improved the effect of Uyghur text classification.

Key words: text classification, information gain, word frequency in class, inverse document frequency, feature selection