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Machine Learning: Paradigms and Methods
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Machine Learning: Paradigms and Methods Paperback - 1990 - 1st Edition

by Jaime Carbonell (Editor)


From the publisher

Having played a central role at the inception of artificial intelligence research, machine learning has recently reemerged as a major area of study at the very core of the subject. Solid theoretical foundations are being constructed. Machine learning methods are being integrated with powerful performance systems, and practical applications; based on established techniques are emerging.Machine Learning unifies the field by bringing together and clearly explaining the major successful paradigms for machine learning: inductive approaches, explanation-based learning, genetic algorithms, and connectionist learning methods. Each paradigm is presented in depth, providing historical perspective but focusing on current research and potential applications.

Contributors
John R. Anderson, L. B. Booker, John. H. Gennari, Jaime G. Carbonell, Oren Etzioni, Doug Fisher, Yolanda Gil, D. E. Goldberg, Gerald E. Hinton, J. H. Holland, Craig A Knoblock, Daniel. R. Kuokka, Pat Langley, David B. Leake, Steve Minton, Jack Mostow, Roger C. Schank, and Jan M. Zytkow

Details

  • Title Machine Learning: Paradigms and Methods
  • Author Jaime Carbonell (Editor)
  • Binding Paperback
  • Edition number 1st
  • Edition 1
  • Pages 404
  • Volumes 1
  • Language ENG
  • Publisher MIT Press, Cambridge, MA, U.S.A.
  • Date 1990-02-23
  • ISBN 9780262530880 / 0262530880
  • Weight 1.15 lbs (0.52 kg)
  • Dimensions 8.9 x 6 x 0.9 in (22.61 x 15.24 x 2.29 cm)
  • Ages 18 to UP years
  • Grade levels 13 - UP
  • Library of Congress subjects Artificial intelligence, Machine learning
  • Library of Congress Catalog Number 89013641
  • Dewey Decimal Code 006.31
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Machine Learning: Paradigms and Methods (Special Issues of  Artificial Intelligence )
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Machine Learning: Paradigms and Methods
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Machine Learning: Paradigms and Methods

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Machine Learning: Paradigms and Methods (Special Issues of  <i>Artificial...
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Machine Learning: Paradigms and Methods (Special Issues of <i>Artificial Intelligence</i>)

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Machine Learning: Paradigms and Methods (Special Issues of  <i>Artificial...
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Machine Learning: Paradigms and Methods (Special Issues of <i>Artificial Intelligence</i>)

by Carbonell, Jaime [Editor]

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