Abstract
A three-way decisions solution based on Bayesian decision theory for filtering spam emails is examined in this paper. Compared to existed filtering systems, the spam filtering is no longer viewed as a binary classification problem. Each incoming email is accepted as a legitimate or rejected as a spam or undecided as a further-exam email by considering the misclassification cost. The three-way decisions solution for spam filtering can reduce the error rate of classifying a legitimate email to spam, and provide a more meaningful decision procedure for users. The solution is not restricted to a specific classifier. Experimental results on several corpus show that the three-way decisions solution can get a better total cost ratio value and a lower weighted error.
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Jia, X., Zheng, K., Li, W., Liu, T., Shang, L. (2012). Three-Way Decisions Solution to Filter Spam Email: An Empirical Study. In: Yao, J., et al. Rough Sets and Current Trends in Computing. RSCTC 2012. Lecture Notes in Computer Science(), vol 7413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32115-3_34
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DOI: https://doi.org/10.1007/978-3-642-32115-3_34
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