Refuting Learning RevisitedAuthors: Wolfgang Merkle and Frank Stephan. Source: Lecture Notes in Artificial Intelligence Vol. 2225, 2001, 299 - 314. Abstract. We consider, within the framework of inductive inference, the concept of refuting learning as introduced by Mukouchi and Arikawa, where the learner is not only required to learn all concepts in a given class but also has to explicitly refute concepts outside the class. In the first part of the paper, we consider learning from text and introduce a concept of limit-refuting learning that is intermediate between refuting learning and reliable learning. We give characterizations for these concepts and show some results about their relative strength and their relation to confident learning.
In the second part of the paper we consider learning from texts
that for some k contain all positive
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