一种基于属性相关性度量的朴素贝叶斯分类模型

A Naive Bayesian Classification Model Based on the Measurement of Attribute with Correlation

本文通过分析属性相关性的度量和属性约简,提出一种基于属性相关性度量的朴素贝叶斯分类模型EANBC。实验结果表明,与朴素贝叶斯分类模型相比,EANBC分类模型具有较高的分类正确率。

On the basis of analyzing the measurement attribute with correlation and reduction of attribute. EANBC （A Naive Bayesian Classifieation Model Based on the measurement of Attribute with Correlation）, is presented. Compared with Naive Bayesian Classification Model, experimental results show that EANBC has higher aeeuraey.