基于KNN的中文文本分类反馈学习研究

A Feedback Learning Study of Chinese Text Categorization Based on KNN

依据KNN分类算法和反馈学习的思想,在分析中文文本分类过程的基础上,给出基于反馈学习的中文文本分类模型和基于KNN的中文文本分类反馈学习过程。通过实验研究反馈学习对中文文本分类模型性能的影响。结果表明,反馈学习是实时变化信息的一种有效的学习方法,它对训练不充分的文本分类器具有很大的改善作用。

Based on KNN classification algorithm and the principle of feedback learning,and after analyzing the Chinese text categorization process, the model of Chinese text categorization based on feedback learning is proposed. Through experiments, the impacter of feedback on the performance of the Chinese text categorization model is studied. The experimental results show that the feedback learning is an effective solution on the real-time change information and can greatly improve the performance of KNN categorization.