000 -LEADER |
fixed length control field |
01252nam a2200217 4500 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
ISBN |
9780387310732 |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
006.4 BIS/P |
100 ## - MAIN ENTRY--AUTHOR NAME |
Personal name |
BISHOP, CHRISTOPHER M. |
245 ## - TITLE STATEMENT |
Title |
PATTERN RECOGNITION AND MACHINE LEARNING |
250 ## - EDITION STATEMENT |
Edition statement |
1st ed. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication |
New York |
Name of publisher |
Springer |
Year of publication |
2006 |
300 ## - PHYSICAL DESCRIPTION |
Number of Pages |
737p. |
490 ## - SERIES STATEMENT |
Series statement |
Information science and statistics |
520 ## - SUMMARY, ETC. |
Summary, etc |
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory. |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical Term |
Computer science |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical Term |
Machine learning |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical Term |
Pattern perception |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical Term |
Pattern recognition systems |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical Term |
Artificial intelligence |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Koha item type |
Books |