Automated knowledge acquisition
Author(s)
Bibliographic Information
Automated knowledge acquisition
（Prentice Hall international series in computer systems science and engineering）
Prentice Hall, c1994
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
This tutorial provides clear explanations of techniques for automated knowledge acquisition. Covers topics such as induction algorithms using decision trees; induction algorithms using progressive rule generation; sub-symbolic learning methods, artificial neural networks; other machine learning paradigms; theoretical considerations; the extraction of rules and concepts using a single-layered Hebbian neural network; BRAINNE - automated knowledge acquisition using multi-layered neural network; and BRAINNE in the real world. For computer professionals who wish to gain a good understanding of automated knowledge acquisition techniques.
Table of Contents
- General considerations
- induction algorithms using decision trees
- induction algorithms using progressive rule generation
- sub-symbolic learning methods - artificial neural networks
- other machine learning paradigms
- theoretical considerations
- the extraction of rules and concepts using a single-layered Hebbian neural network
- BRAINNE - automated knowledge acquisition using multi-layered neural network
- BRAINNE in the real world.
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