Abstract
In the area of inductive learning, generalization is a main operation. Already in the early 1970's Plotkin described algorithms for computation of least general generalizations of clauses under θ-subsumption. However, there is a type of generalizations, called roots of clauses, that is not possible to find by generalization under θ-subsumption. This incompleteness is important, since almost all inductive learners that use clausal representation perform generalization under θ-subsumption.
In this paper a technique to eliminate this incompleteness, by reducing generalization under implication to generalization under θ-subsumption, is presented. The technique is conceptually simple and is based on an inference rule from natural deduction, called or-introduction. The technique is proved to be sound and complete, but unfortunately it suffers from complexity problems.
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Idestam-Almquist, P. (1993). Generalization under implication by using or-introduction. In: Brazdil, P.B. (eds) Machine Learning: ECML-93. ECML 1993. Lecture Notes in Computer Science, vol 667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56602-3_127
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DOI: https://doi.org/10.1007/3-540-56602-3_127
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