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.
CITATION STYLE
Quinlan, J. R. (1983). Learning Efficient Classification Procedures and Their Application to Chess End Games. In Machine Learning (pp. 463–482). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-12405-5_15
Mendeley helps you to discover research relevant for your work.