摘要
构造了一种新的属性间相关性度量方法,提出了改进属性加权的朴素贝叶斯分类模型。经实验证明,提出的朴素贝叶斯分类模型明显优于张舜仲等人提出的分类模型。
To improve attribute weighted the naive Bayesian classifier model,a new measurement method of the inter-related weighted attributes is structured.The experiment proves that the naive Bayesian classifier model is superior to the classification model proposed by Zhang Shun-zhong et al.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第4期132-133,141,共3页
Computer Engineering and Applications
关键词
属性加权
朴素贝叶斯
分类模型
相关性度量
attribute weighted
naive Bayesian
classification model
relevant measure
