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.
Pattern Recognition and Machine Learning, 1st Edition
Reader's Guide. Recognition and Learning By a Computer. Representing Information. Generation and Transformation of Representations. Pattern Feature Extraction. Pattern Feature Extraction. Pattern Understanding Methods. Learning Concepts. Learning Procedures. Learning Based on Logic. Learning Procedures. Learning Based on Logic. Learning By Classification and Discovery. Learning By Neural Network. Appendix. Answers to Exercises. Chapter Summaries, Keywords, And Exercises. Chapter References. Index.