计算机工程与应用Issue(20)：118-121,4.DOI:10.3778/j.issn.1002-8331.1201-0299
不均衡数据集上文本分类方法研究
Study of text categorization on imbalanced data
摘要
Abstract
Class imbalance problems are often encountered in real application of automatic text classifications. From the view of the optimistic feature selection methods and the improvement of classifiers, a new text classification method on imbalanced data set is proposed. The positive and negative correlation between items and categorizations are combined with the strength of class information in the aspect of the feature selection scheme. Then on the data layer, the imbalanced characters of the training corpus are filtered by data resampling methods in order to reduce the effect on the classification. Experimental results show that the new approach can achieve better performance.关键词
特征选择/CHI统计/文本分类/不均衡数据集/重取样Key words
feature selection/CHI statistical approach/text categorization/imbalanced data/resampling分类
信息技术与安全科学引用本文复制引用
谢娜娜,房斌,吴磊..不均衡数据集上文本分类方法研究[J].计算机工程与应用,2013,(20):118-121,4.基金项目
国家自然科学基金（No.61173129）。 （）
