Abstract
The MLEM2 algorithm is a rule induction algorithm in which rule induction, discretization, and handling missing attribute values are all conducted simultaneously. In this paper two versions of the MLEM2 algorithm are compared: the first version of MLEM2 induces rules that may contain two conditions with the same numerical attribute and different intervals. The second version of MLEM2 induces rules with merged conditions associated with numerical attributes, i.e., all conditions are related to different attributes. For completeness, experiments on the original LEM algorithm with discretization as a preprocessing are also included. The performance, in terms of accuracy, for all three algorithms is approximately the same (for any two of them the difference in performance is not statistically significant).
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