Effectiveness and Limitations of Statistical Spam Filters

Details Effectiveness and Limitations of Statistical Spam Filters Effectiveness and Limitations of Statistical Spam Filters

2009-10-14

arxiv.org/abs/0910.2540v1

International Conference on New Trends in Statistics and Optimization, Organized by Department of Statistics, University of Ka

Computer Science

Learning

International Conference on New Trends in Statistics and Optimization, Organized by Department of Statistics, University of Ka

Scientific paper

In this paper we discuss the techniques involved in the design of the famous statistical spam filters that include Naive Bayes, Term Frequency-Inverse Document Frequency, K-Nearest Neighbor, Support Vector Machine, and Bayes Additive Regression Tree. We compare these techniques with each other in terms of accuracy, recall, precision, etc. Further, we discuss the effectiveness and limitations of statistical filters in filtering out various types of spam from legitimate e-mails.

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