Re-examination on lam% in spam filtering
Haoliang Qi, Muyun Yang, Xiaoning He, Sheng Li · 2010
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.