Computational Linguistics 12(3):175-204

Machine Learning, 1, 11–46.

The technology for building knowledge-based systems by inductive inference from examples hasbeen demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of overcoming it are compared. The paper concludes with illustrations of current research directionsMachine Learning, 1, p. 81-106

Also see the . New York: Springer Verlag, (2nd edition 1986, 3rd edition 1990, 4th edition 1995)

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

Kluwer Academic Publishers, 1986

In AAAI-86, Vol. 1, pp. 210–214.

Artificial Intelligence, 28:127-162

Artificial Intelligence, 28 (2), 225-33.

CMU-CS-85-115, Carnegie Mellon University. Reprinted in Michalski, R. S., Carbonell, J. G., and Mitchell, T. M., (Eds.), Machine Learning: An Artificial Intelligence Approach, volume 2, chapter 14, pages 371-392. Morgan Kaufmann Publishers. Derivational analogy, a method of solving problems based on the transfer of past experience to new probiem situations, is discussed in the context of other general approaches to problem solving. The experience transfer process consists of recreating lines of reasoning, including decision sequences and accompanying justifications, that proved effective in solving particular problems requiring similar initial analysis. The role of derivational analogy in case-based reasoning and in automated expertise acquisition is discussed.