Knowledge acquisition and machine learning : theory, methods, and applications
著者
書誌事項
Knowledge acquisition and machine learning : theory, methods, and applications
Academic Press, c1933 [i.e. c1993]
大学図書館所蔵 件 / 全19件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Bibliography: p. 281-294
Includes indexes
Author: Katharina Morik, Stefan Wrobel, Jörg-Uwe Kietz and Werner Emde
内容説明・目次
内容説明
For graduate-/research- level students and professors, this book integrates machine learning with knowledge acquisition to overcome the problems of building models for knowledge-based systems to maintain them successfully. It also reports on BLIP and MOBAL systems developed over the last decade, which illustrate a particular way of unifying knowledge acquisition and machine learning. Practically-orientated, theoretical skills have been used and tested in real-world applications.
目次
The Knowledge Acquisition Framework. The Knowledge Representation Environment. The Inference Im-2. The Sort Taxonomy. The Predicate Structure. Model-Driven Rule Discovery. Knowledge Revision. Concept Formation. Practical Experiences. Bibliography. Author Index. Name Index. Subject Index.
「Nielsen BookData」 より