The m-estimate measure (with k = 2 and p+ = 0.2).
Consider a training set that contains 100 positive examples and 400 negative
examples. For each of the following candidate rules,
R1: A ?? + (covers 4 positive and 1 negative examples),
R2: B ?? + (covers 30 positive and 10 negative examples),
R3: C ?? + (covers 100 positive and 90 negative examples),
determine which is the best and worst candidate rule according to:
The m-estimate measure of the rules are 62.86% (for R1), 73.38% (for
R2), and 52.3% (for R3), respectively. Therefore R2 is the best candi-
date and R3 is the worst candidate according to the m-estimate mea-
sure.
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