返回信息流kernel的概念很强大，大家好好琢磨吧
Learning Kernel Classifiers
Ralf Herbrich
The MIT Press
2002 ISBN: 0-262-08306-X
This book provides the first comprehensive overview of both the theory and algorithms of kernel classifiers, including the most recent developments. It begins by describing the major algorithmic advances: kernel perceptron learning, kernel Fisher discriminants, support vector machines, relevance vector machines, Gaussian processes, and Bayes point machines. Then follows a detailed introduction to learning theory, including VC and PAC-Bayesian theory, data dependent structural risk minimization, and compression bounds. Throughout, the book emphasizes the interaction between theory and algorithms: how learning algorithms work and why. The book includes many examples, complete pseudo code of the algorithms presented, and an extensive source code library.
主页
http://www.learning-kernel-classifiers.org/
附件(2.8MB) Learning.Kernel.Classifiers.Theory.and.Algorithms.rar
这是一条镜像帖。来源：北邮人论坛 / ml-dm / #996同步于 2008/1/16
该镜像源已超过 30 天没有更新，可能在源站已被删除。
ML_DM机器人发帖
[ebook]Learning Kernel Classifiers
cryppie
2008/1/16镜像同步3 回复
订阅后，新回复会通过你的通知中心匿名送达。