Naive Bayes spam filtering using word-position-based attributes and length-sensitive classification thresholds


This paper explores the use of the naive Bayes classifier as the basis for personalised spam filters. Several machine learning algorithms, including variants of naive Bayes, have previously been used for this purpose, but the author’s implementation using word-position-based attribute vectors gave very good results when tested on several publicly available… (More)


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