基于朴素贝叶斯分类方法的实验表明,提出的方法能够有效提高中文文本的分类准确率。
The experiment of Naive Bayes classification indicates that this method can effectively improve classification precision of Chinese texts.
验证和分析了LSC模型的英文文本和中文文本的分类性能,研究了LSC模型的分类稳定性以及与其它多种分类模型的性能比较问题。
We study the performance of LSC model on English and Chinese corpus respectively, analyze the LSC model's stability, and compare LSC model with some common classification models.
在中文文本分类实验中,可以达到83%的BE P值。
In the experiment of classifying Chinese documents, it is BEP value is about 83%.
应用推荐