机译:利用概率主题模型改善班级不平衡下的文本分类
School of Computer Science and Technology, P.O. Box 4, Hefei, Anhui 230027, PR China;
School of Computer Science and Technology, P.O. Box 4, Hefei, Anhui 230027, PR China;
Department of Management Science and Information Systems, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901-8554, USA;
School of Computer Science and Technology, P.O. Box 4, Hefei, Anhui 230027, PR China;
School of Computer Science and Technology, P.O. Box 4, Hefei, Anhui 230027, PR China;
class imbalance; rare class analysis; text categorization; probabilistic topic model; noisy data;
机译:使用散点图来理解和改进用于文本分类和检索的概率模型
机译:通过使用主题模型改善文本分类
机译:基于概率主题模型的文本文档分类
机译:基于K-均值和卡方特征选择的改进Native Bayes分类器用于文本不平衡分类
机译:文本主题的概率主题建模和分类概率PCA。
机译:文本分类中考虑不平衡问题的改进特征选择方法
机译:使用散点图理解和改进概率模型进行文本分类和检索