摘要
分析贝叶斯文本分类算法的不足,提出相应的改进算法。放宽朴素贝叶斯文本分类模型中的属性独立性假设,采用一种改进的基于贝叶斯定理的文本分类模型"树桩网络",改进朴素贝叶斯文本分类模型。实验证明,改进后的文本分类模型适合于文本分类的需要,改善了原有分类器的性能。
This paper analyzes the shortcomings of Bayes and puts forward a better method to improve it. It releases attribute independence assumption of Naive Bayes text classifier. An improved text classification model based on Bayes theorem called stump network is presented to amend the Naive Bayes text classifier. Experiment shows that the revised text categorization model meets the need of text categorization, and improves the performance of former one.
出处
《计算机工程》
CAS
CSCD
北大核心
2009年第16期201-202,205,共3页
Computer Engineering
关键词
文本分类
朴素贝叶斯
属性独立性假设
树桩网络
text classification
Naive Bayes
attribute independence assumption
stump network
