基于weka的分类算法，用于weka拓展应用。朴素贝叶斯模型发源于古典数学理论，有着坚实的数学基础，以及稳定的分类效率。同时，该算法所需估计的参数很少，对缺失数据不太敏感，算法也比较简单。理论上，与其他分类方法相比具有最小的误差率。,Based on the classification algorithm weka, weka develop applications for. Naive Bayes model originated in the classical mathematical theory, has a solid mathematical basis, as well as the stability of the classification efficiency. At the same time, the algorithm estimates the parameters required for small, less sensitive to missing data, the algorithm is also relatively simple. In theory, when compared with other classification methods with the smallest margin of error.