文档介绍：Pattern Recognition and Machine Learning
Solutions to the Exercises: Web-Edition
Markus Svensen´ and Christopher M. Bishop
Copyright c 2002–2009
This is the solutions manual (web-edition) for the book Pattern Recognition and Machine Learning
(PRML; published by Springer in 2006). It contains solutions to the . This release
was created September 8, 2009. Future releases with corrections to errors will be published on the PRML
web-site (see below).
The authors would like to express their gratitude to the various people who have provided feedback on
earlier releases of this document. In particular, the “Bishop Reading Group”, held in the Visual Geometry
Group at the University of Oxford provided ments and suggestions.
The authors e ments, questions and suggestions about the solutions as well as reports on
(potential) errors in text or formulae in this document; please send any such feedback to
prml-fb@
Further information about PRML is available from
http://research./ cmbishop/PRML
∼
Contents
Contents 5
Chapter 1: Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Chapter 2: Probability Distributions . . . . . . . . . . . . . . . . . . . . 20
Chapter 3: Linear Models for Regression . . . . . . . . . . . . . . . . . . 35
Chapter 4: Linear Models for Classification . . . . . . . . . . . . . . . . 41
Chapter 5: works . . . . . . . . . . . . . . . . . . . . . . . . 46
Chapter 6: Kernel Methods . . . . . . . . . . . . . . . . . . . . . . . . . 54
Chapter 7: Sparse Kernel Machines . . . . . . . . . . . . . . . . . . . . . 59
Chapter 8: Graphical Models . . . . . . . . . . . . . . . . . . . . . . . . 63
Chapter 9: Mixture Models and EM . . . . . . . . . . . . . . . . . . . . 68
Chapter 10: Approximate Inference . . . . . . . . . . . . . . . . . . . . . 72
Chapter 11: Sampling Methods . . . . . . . . . . . . . . . . . . . . . . . 83
Chapter 12: Continuous Latent Variables . . . . . . . . . . . . . . . . . . 85