计算机科学 ›› 2016, Vol. 43 ›› Issue (10): 206-210.doi: 10.11896/j.issn.1002-137X.2016.10.039
王杰,李德玉,王素格
WANG Jie, LI De-yu and WANG Su-ge
摘要： 非平衡数据中样本数量的不平衡分布往往伴随着特征分布的不平衡,在多数类文本中经常出现的特征,在少数类中却很少出现。针对非平衡数据特征分布的特点,提出了一种新的双边fisher特征选择算法TSF。该方法通过显式地组合正相关和负相关特征,缓解了特征层面的非平衡性,较好地表示了文本的信息。TSF方法在图书评论和COAE2014微博非平衡数据上进行实验,结果验证了该方法是可行的。
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