Skimmed Classi ers
نویسندگان
چکیده
Most Inductive Logic Programming (ILP) systems use a greedy covering algorithm to nd a set of clauses that best model positive examples. This set of clauses is called a theory and can be seen as an ensemble of clauses. It turns out that the search for a theory within the ILP system is very time consuming and often yields overly complex classi ers. One alternative approach to obtain a theory is to use the ILP system to non deterministically learn one clause at a time, several times, and to combine the obtained clauses using ensemble methods.
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