文档介绍：Pattern Recognition and Machine Learning
Solutions to the Exercises: Web-Edition
Markus Svensen´ and Christopher M. Bishop
Copyright c 2002–2007
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 August 3, 2007; eventual 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
pre-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 Markus Svens´en,
******@.
Further information about PRML is available from:
http://research./ cmbishop/PRML
∼
Contents
Contents 5
Chapter 1: Pattern Recognition . . . . . . . . . . . . . . . . . . . . . . . 7
Chapter 2: Density Estimation . . . . . . . . . . . . . . . . . . . . . . . 19
Chapter 3: Linear Models for Regression . . . . . . . . . . . . . . . . . . 34
Chapter 4: Linear Models for Classification . . . . . . . . . . . . . . . . 41
Chapter 5: works . . . . . . . . . . . . . . . . . . . . . . . . 46
Chapter 6: Kernel Methods . . . . . . . . . . . . . . . . . . . . . . . . . 53
Chapter 7: Sparse Kernel Machines . . . . . . . . . . . . . . . . . . . . . 59
Chapter 8: Probabilistic Graphical Models . . . . . . . . . . . . . . . . . 63
Chapter 9: Mixture Models . . . . . . . . . . . . . . . . . . . . . . . . . 68
Chapter 10: Variational Inference and EM . . . . . . . . . . . . . . . . . 72
Chapter 11: Sampling Methods . . . . . . . . . . . . . . . . . . . . . . . 82
Chapter 12: Latent Variables . . . . . . . . . . . . . .