Bayesian classification model based on attribute correlation analysis 基于属性相关性分析的贝叶斯分类模型
According to the criteria , the advancement of bayesian classification is evident 综合这几个指标,贝叶斯分类算法的优点较为突出。
The bayesian classification and identification method based on normal - inverted wishart prior distribution 先验分布的贝叶斯分类识别方法研究
The often - used classification is classification by decision tree induction , bayesian classification and bayesian belief networks , k - nearest neighbor classifiers , rough set theory and fuzzy set approaches 分类算法常见的有判定树归纳分类、贝叶斯分类和贝叶斯网络、 k -最临近分类、粗糙集方法以及模糊集方法。
There are many techniques for data classification such as decision tree induction , bayesian classification and bayesian belief networks , association - based classification , genetic algorithms , rough sets , and k - nearest neighbor classifiers 挖掘分类模式的方法有多种,如决策树方法、贝叶斯网络、遗传算法、基于关联的分类方法、粗糙集和k -最临近方法等等。