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A Compendium of Machine Learning I: Symbolic Learning (PB)
Out of Print
Price £30, $43
ISBN 9781567501797
Paperback 353 pages

Published May 1996
Imprint: Ablex
Books by Garry Briscoe
Books by Terry Caelli
Books in Other Subject Areas

Machine learning is a relatively new branch of artificial intelligence. The field is currently undergoing a significant period of growth, with many new areas of research and development being explored. However, at present there is a general lack of texts which take an overall view of Machine Learning the basic algorithms and themes which occur (and reoccur) throughout the various research streams. In this text, the authors take a broad brush view of the field in an attempt to bring together many of the results that have been achieved, presenting a general taxonomy of the field and the various key representative algorithms.

 

Contents

• Introduction
• Definitions, Paradigms, Taxonomies
SYMBOLIC EMPIRICAL LEARNING/SEL
• Introduction
• Learning from Examples
• Decision Trees
• Version Spaces
• Covering Algorithms
• Inductive Logic Programming
• Bias
• Conceptual Clustering
• Discovery
• Appendium: Other SELTopics
ANALYTlCAL LEARNING
EBL
• Introduction
• Learning Composite Rules
• Learning Search Control Knowledge
• Appendium: Other EBL Topics
EXEMPLARS, CASE-BASED AND ANALOGY
• Exemplar-Based/Case-Based Reasoning
• Appendium: Other Exemplar
• Case-Based Topics
• Analogy
• Appendium: Other Analogy Topics
INTEGRATED LEARNING SYSTEMS
• Introduction to Integrated Systems
• Overly-General or Overly-Specific Theories
• Systems for General Theory Revision
• Appendium: Other Integrated System Topics
FORMAL ANALYSIS-THEORY
• Machine Learning Theory
• Appendium: Other Formal Theory Topics
APPENDICES
• Glossary
• Electronic Information Sources

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1 comments:
demo  Said...

Machine learning is a relatively new branch of artificial intelligence. The field is currently undergoing a significant period of growth, with many new areas of research and development being explored. However, at present there is a general lack of texts which take an overall view of Machine Learning the basic algorithms and themes which occur (and reoccur) throughout the various research streams. In this text, the authors take a broad brush view of the field in an attempt to bring together many of the results that have been achieved, presenting a general taxonomy of the field and the various key representative algorithms.

May 11, 2009 13:35
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