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Introduction to machine learning / Yves Kondratoff.
By: Kodratoff, Yves
.
Material type: 
BookPublisher: London : Pitman, 1988Description: 298 p. : ill. ; 25 cm. + pbk.ISBN: 0273087967.Subject(s): Machine learningDDC classification: 006.31
| Item type | Current library | Call number | Copy number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|
| General Lending | MTU Bishopstown Library Store Item | 006.31 (Browse shelf(Opens below)) | 1 | Available | 00126376 |
Total holds: 0
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Enhanced descriptions from Syndetics:
A description of the state of the art in machine learning (ML) which includes exercises and examples designed to give the reader a firm grasp of the concepts and techniques of the subject. The results of a number of leading ML researchers are also explored and presented for study.
Includes bibliographical references and index.
Table of contents provided by Syndetics
- 1 Why Machine Learning and AI: The Contributions of AI to Learning Techniques
- 2 Theoretical Foundations for Machine Learning
- 3 Representation of Complex Knowledge by Clauses
- 4 Representation of Knowledge about Actions and the Addition of New Rules to a Knowledge Base
- 5 Learning by Doing
- 6 A Formal Presentation of Version Spaces
- 7 Explanation-Based Learning
- 8 Learning by Similarity Detection: The Empirical Approach
- 9 Learning by Similarity Detection: The 'Rational' Approach
- 10 Automatic Construction of Taxonomies: Techniques for Clustering
- 11 Debugging and Understanding in Depth: The Learning of Micro-Worlds
- 12 Learning by Analogy
- Appendix 1 Equivalence Between Theorems and Clauses
- Appendix 2 Synthesis of Predicates
- Appendix 3 Machine Learning in Context