Experiment Research on Spam Filter Classifier Based on Naive Bayesian Algorithm
Teng Lv, Ping Yan, Hongwu Yuan, Weimin He · 2021
These days, we are bombarded with endless spam e-mails. The harm of spam to our daily life includes: spam usually has unhealthy contents, which requires a vast waste of bandwidth to transfer spam, and vast waste of space to store spam. In this paper, main technologies to identify and block spam are analyzed including information filtering, blacklist and white list, and intention analysis. Then a classifier based on naive Bayesian algorithm to determine whether an e-mail is a spam or not is given. Finally, experiments of different settings are conducted and analyzed to show how different settings affects the accuracy, precision, recall, and f1_ score of dataset.