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

贝叶斯分类算法，构造朴素贝叶斯分类器，对给定的中文文本进行分类,Bayesian classification algorithm, Naive Bayes classifier structure of a given Chinese text classification

朴素贝叶斯分类算法,可以用来进行分类bayes -Naive Bayesian classification algorithm can be used to classify the Bayes

JAVA写的垃圾邮件过滤器,基于朴素贝叶斯算法，用NetBean生成的界面（须JDK1.6），适用于对手机短信，邮箱邮件，日记等一些txt文件进行分类，测试率达90 以上。-JAVA to write spam filters, based on the Naive Bayes algorithm, using NetBean generated interface (to be JDK1.6), applies to SMS, E-mail e-mail, diary and some oth

分类算法的java实现，包括KNN算法，朴素贝叶斯算法等-Classification algorithm to achieve by java, including KNN algorithm, Naive Bayes algorithm