Research On Spam Filter Based On Improved Naive Bayes and KNN Algorithm

In the field of data mining and pattern recognition, classification is a very important core technology. This paper present two kinds of improved classification algorithm. Using the improved Naive Bayes (NB) and KNN algorithm structure classifier to filter normal mail and spam. Improved NB algorithm can dynamically adjust the threshold k, reduces the mail mistake rate. Center vector method is introduced into the similarity calculation formula of KNN, better reflect the interrelation between the text and categories. Finally, improvedNB algorithm and KNN algorithm make comparison and analysis, it is concluded that the effective experimental results.