Abstract
A series of experiments dealing with the discovery of efficient classification procedures from large numbers of examples is described, with a case study from the chess end game king-rook versus king-knight. After an outline of the inductive inference machinery used, the paper reports on trials leading to correct and very fast attribute-based rules for the relations lost 2-ply and lost 3-ply. On another tack, a model of the performance of an idealized induction system is developed and its somewhat surprising predictions compared with observed results. The paper ends with a description of preliminary work on the automatic specification of relevant attributes.
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© 1983 Springer-Verlag Berlin Heidelberg
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Quinlan, J.R. (1983). Learning Efficient Classification Procedures and Their Application to Chess End Games. In: Michalski, R.S., Carbonell, J.G., Mitchell, T.M. (eds) Machine Learning. Symbolic Computation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-12405-5_15
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DOI: https://doi.org/10.1007/978-3-662-12405-5_15
Publisher Name: Springer, Berlin, Heidelberg
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