Techniques in computational learning : an introduction
著者
書誌事項
Techniques in computational learning : an introduction
（Chapman and Hall computing）
Chapman & Hall, 1992
- : U.S.
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内容説明・目次
内容説明
This is an introduction to the theory and practice of computational learning. the author describes in detail both the connectionist techniques ussed in computing with artificial neural networks and the symbolist techniques generally used in artificial intelligence. These techniques are presented in a common framework within which the behaviour of learning mechanisms is analyzed geometrically. This treatment is suitable for the analysis of computational learning, allowing results to be presented in an accessible form using pictures and diagrams. As well as detailed discussion of the principle theories and techniques, problems are given at the end of each chapter and comprehensive reading lists are included. these features make the book particularly suitable for students approaching the subject for the first time.
目次
- Candidate elimination and the version space
- focussing
- AQ11
- information theory
- ID3
- unsupervised learning by clustering
- LEX and explanation-based learning
- introduction to connectionism
- the linear threshold unit
- learning by error-reduction
- the pattern associator
- back-propagation
- learning to diagnose heart disease
- analyzing internal representations
- constructive learning procedures
- the WISARD net
- competitive learning and the kohonen net
- the hopfield net
- the boltzman machine
- discussion.
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