Effectiveness and Limitations of Statistical Spam Filters

Effectiveness and Limitations of Statistical Spam Filters

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 te...

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Veröffentlicht in:arXiv.org 2009-10
Hauptverfasser: Banday, M Tariq, Jan, Tariq R
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Bayesian analysis
Regression analysis
Spamming
Statistical analysis
Support vector machines
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description 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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subjects Bayesian analysis
Regression analysis
Spamming
Statistical analysis
Support vector machines
title Effectiveness and Limitations of Statistical Spam Filters
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