Learning Logical Definitions from Relations
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foil is a system that learns Horn clauses from data expressed as relations, based on ideas that have proved effective in attribute-value learning systems, but extends them to a first-order formalism.Abstract:
This paper describes FOIL, a system that learns Horn clauses from data expressed as relations. FOIL is based on ideas that have proved effective in attribute-value learning systems, but extends them to a first-order formalism. This new system has been applied successfully to several tasks taken from the machine learning literature.read more
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References
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Induction of Decision Trees
TL;DR: In this paper, an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail, is described, and a reported shortcoming of the basic algorithm is discussed.
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TL;DR: The methodology used to construct tree structured rules is the focus of a monograph as mentioned in this paper, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
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Simplifying decision trees
TL;DR: Techniques for simplifying decision trees while retaining their accuracy are discussed, described, illustrated, and compared on a test-bed of decision trees from a variety of domains.
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The CN2 Induction Algorithm
Peter Clark,Tim Niblett +1 more
TL;DR: A description and empirical evaluation of a new induction system, CN2, designed for the efficient induction of simple, comprehensible production rules in domains where problems of poor description language and/or noise may be present.