摘要
基于机器学习的垃圾邮件过滤方法相较于传统方法有更好的效果。文本表示方法的好坏会对分类算法产生影响。加权LDA模型在传统LDA模型的基础上引入词权重机制,通过这种方法获得的文本表示联合SVM分类器对邮件进行过滤,获得较好的分类效果。通过对比实验也验证这种方法的正确性和可靠性。
Spam filtering method based on machine learning has a better result than the traditional filtering methods. Text representation affects the result of classification algorithm. Adopts the term weighted LDA on the basis of LDA model, uses term weighted LDA model and SVM to filter spare, so as to get a good classification result. The contrast experiment also verifies the validity and reliability of the method.
