Rule induction from data with numerical attributes must be accompanied by discretization. Our main objective was to compare two discretization techniques, both based on cluster analysis, with a new rule induction algorithm called MLEM2, in which ...
Rules have a number of desirable properties. It is easy to understand, infer new knowledge, and communicate with other inference systems. One weakness of the previous rule induction systems is that they only find rules within a knowledge base (KB) and ...
This paper proposes a new supervised induction algorithm, IGR, that uses each training instances as a guide of rule induction. IGR learns a set of if-then rules by inducing a pseudo-optimun classification rule for each training instance. IGR weighs the ...
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