摘要
朴素贝叶斯方法是数据库分类知识挖掘领域一项基本技术,具有广泛的应用。朴素贝叶斯分类器的计算过程只有在完全数据库中才成立,而基于相似关系的粗糙集模型具有处理空值的功能,并且提供了属性离散化和约简技术,可以改善属性间的依赖关系。实验结果表明,基于粗集理论的贝叶斯分类方法改善了贝叶斯分类方法中属性之间独立的限制,简化了挖掘模型,使挖掘性能具有明显的优化。
Naive Bayesian method is basic technology that has been applied widely for class know- ledge discover in database.The naive Bayesian classifier can produce competitive predictive accuracy in many learning tasks,but it can be used only in compiete databases.The rough set model based on similarity relationship can process the null,and it has attribute discretization and reduction functions SO that the dependency of the condition feature and the decision-making feature can be improved.Experiment result indicates that rough set based Bayesian class model can ameliorate the restriction of attributions independence in naive Bayesian method,simplify class mode mining model and optimize markedly performance of mining arithmetic.
出处
《科技信息》
2010年第09X期63-64,共2页
Science & Technology Information
