Re-examination on lam% in spam filtering

Authors:
Haoliang Qi;Muyun Yang;Xiaoning He;Sheng Li
Affiliations:
Heilongjiang Institute of Technology, Harbin, China;Harbin Institute of Technology, Harbin, China;Harbin Institute of Technology, Harbin, China;Harbin Institute of Technology, Harbin, China
Venue:
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Year:
2010

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Abstract

Logistic average misclassification percentage (lam%) is a key measure for the spam filtering performance. This paper demonstrates that a spam filter can achieve a perfect 0.00% in lam%, the minimal value in theory, by simply setting a biased threshold during the classifier modeling. At the same time, the overall classification performance reaches only a low accuracy. The result suggests that the role of lam% for spam filtering evaluation should be re-examined.