Ross Quinlan (1979). Discovering Rules by Induction from Large Collections of Examples. Expert Systems in the Micro-electronic Age, pp. 168-201. Edinburgh University Press (Introducing ID3)
Ross Quinlan (1982). Semi-Autonomous Acquisition of Pattern-Based Knowledge. Introductory Readings in Expert Systems, pp. 192-207. Gordon & Breach, New York. ISBN 0677163509.
Ross Quinlan (1983, 1985). Learning efficient classification procedures and their application to chess end games. Machine Learning: An Artificial Intelligence Approach [12][13][14]
Ross Quinlan (1986). Induction of Decision Trees. Machine Learning 1, 1, 81-106
Ross Quinlan (1986). The Effect of Noise on Concept Learning. Machine Learning: An Artificial Intelligence Approach, Vol. 2 [15]
^Ross Quinlan (1983). Learning efficient classification procedures and their application to chess end games. In Machine Learning: An Artificial Intelligence Approach, pages 463–482. Tioga, Palo Alto
an Australian computer scientist and researcher in machine learning, data mining, and decision theory. He currently runs his company RuleQuest Research [1], and was affiliated with the University of Sydney, the University of Technology Sydney, the University Of New South Wales and the RAND Corporation.
Based on the concept learning [2] by Earl B. Hunt [3] as used in decision tree learning, Ross Quinlan invented the tree induction algorithms Iterative Dichotomiser 3 (ID3) [4] [5] and their successors C4.5, and C5.0 [6] [7]. One application of these algorithms is to discover classifications rules for chess endgames, as shown with KRKN and ID3 in Learning efficient classification procedures and their application to chess end games [8] .
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