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Learning and Generalization of Characteristic Descriptions: Evaluation Criteria and Comparative Review of Selected Methods

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Proceedings of the Sixth International Joint Conference on Artificial Intelligence. .

Abstract

Some recent work in the area of learning structural descriptions from examples is reviewed in light of the need in many diverse disciplines for programs which can perform conceptual data analysis. Such programs describe complex data in terms of logical, functional, and causal relationships which cannot be discovered using traditional data analysis techniques. Various important aspects of the problem of learning structural . descriptions are examined and criteria for evaluating current work is presented. Methods published by Buchanan, et.al.[1-3t20), Hayes-Roth [6-9), and Vere [22-25], are analyzed accordiag to these criteria and comparea to a method developed by the authors. Finally some goals are suggested for future research.

Thomas G. Dietterich, and Ryszard S. Michalski. 1979. Learning and Generalization of Characteristic Descriptions: Evaluation Criteria and Comparative Review of Selected Methods. In Proceedings of the Sixth International Joint Conference on Artificial Intelligence, IJCAI-79. IJCAI, https://ijcai.org/proceedings/1979/50
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