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Machine Learning


   bib/       Machine Learning Bibliographies
   database/  Machine Learning Databases
   mail/      Machine Learning Mailing List Archives
   systems/   Machine Learning Software Packages
This directory contains software and materials concerning machine learning.
References: J. G. Carbonell, editor, "Machine Learning: Paradigms and Methods", MIT Press, Cambridge, MA 1990. Jude W. Shavlik and Thomas D. Dietterich, editors, "Readings in Machine Learning", Morgan Kaufmann Publishers, 1990, 853 pages. ISBN 1-55860-143-0, $49.95. Tom Mitchell, Jaime G. Carbonell, and Ryszard S. Michalski, "Machine Learning: A guide to current research", Kluwer Academic Publishers, Boston, 1986. [A bit out of date.] Alan Hutchinson, "Algorithmic Learning", Oxford University Press, Oxford, England, 1994. 434 pages, ISBN 0-19-853848-0 paper (27.50 Sterling), ISBN 0-19-853766-2 hardcover (55.00 Sterling). Corrections and additions are available by anonymous ftp from [] [See also the article on Machine Learning from the Encyclopedia of Artificial Intelligence, pages 464-485.] Quinlan, J. Ross, "Induction of Decision Trees", Machine Learning 1(1):81-106, 1986. [Decision Trees] Quinlan, J. Ross, "C4.5: Programs for Machine Learning", Morgan Kaufmann Publishers, 1992. ISBN 1-55860-238-0. $44.95 US, $49.45 International. For a slight additional charge ($25), the book comes with software (ISBN 1-55860-240-2). For software only, (ISBN 1-55860-239-9) $34.95 US, $38.45 International. [Decision Trees] Fisher, D.H., "Knowledge Acquisition Via Incremental Conceptual Clustering", Machine Learning 2:139-172, 1987. (Probabilistic clustering methods.) [Probabilistic Clustering] Clancey, W.J., "Classification Problem Solving", Proceedings of the National Conference on Artificial Intelligence, 49-55, Los Altos, CA, Morgan Kaufmann. 1984. [Probabilistic Clustering] Tom M. Mitchell, "Generalization as Search", Artificial Intelligence 18:203-226, 1982. [Version Spaces] Laird J.E., Rosenbloom, P.S. and Newell, A., "Chunking in SOAR: The Anatomy of a General Learning Mechanism", Machine Learning 1:1-46, 1986. [Chunking] Mitchell, Tom M., Keller, R. M., and Kedar-Cabelli, S. T., "Explanation-based learning: A unified view", Machine Learning 1:47-80, 1986. [Explanation-Based Learning] Carbonell, J. G., "Derivational analogy: A theory of reconstructive problem solving and expertise acquisition." In R.S. Michalski, Jaime G. Carbonell, and Tom M. Mitchell, editors, Machine Learning: An Artificial Intelligence Approach, Morgan Kaufmann Publishers, San Mateo, CA, 1986. [Derivational Analogy] Leslie G. Valiant, "A theory of the learnable", Communications of the ACM, 27(11):1134--1142, 1984. [Theoretical Results] Haussler, D., "Quantifying Inductive Bias: AI Learning Algorithms and Valiant's Learning Framework", Artificial Intelligence, 36:177-221, 1988. [Theoretical Results] CD-ROM: Prime Time Freeware for AI, Issue 1-1 Keywords: AI Software Packages, Machine Learning, Software Packages
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