Pattern Recognition and Machine Learning

Front Cover
Morgan Kaufmann, 1992 - Computers - 407 pages
0 Reviews
This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.
  

What people are saying - Write a review

We haven't found any reviews in the usual places.

Contents

Recognition and Learning by a Computer
1
Representing Information
13
Generation and Transformation
49
Pattern Feature Extraction
89
Pattern Understanding Methods
141
Learning Concepts
177
Learning Procedures
205
Learning Based on Logic
235
Learning by Classification and Discovery
265
Learning by Neural Networks
297
Appendix
337
Answers
357
Bibliography
387
Index
403
Copyright

Common terms and phrases

Popular passages

Page 393 - DH Ballard: Generalizing the Hough transform to detect arbitrary shapes, Pattern Recognition, vol. 13, pp. 111-122, 1981.
Page 399 - Induction of decision Trees," Machine Learning, vol. 1, pp. 81-106, 1986.

References to this book

All Book Search results »

About the author (1992)

Anzai (Keio University)

Bibliographic information