Learning with Kernels

出版者:The MIT Press

作者:Bernhard Schlkopf

页数:648

出版时间:2001-12-15

价格:USD 79.00

装帧:Hardcover

isbn号码:9780262194754

丛书系列:Adaptive Computation and Machine Learning

图书标签:机器学习核方法MachineLearningKernels支持向量机与核方法kernel数学支持向量机

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics.Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

读后感

It is an excellent book about learning with kernels. Another issue related to kernels is learning kernels, not learning with kernels. Kernel learning has a long history in research and is important in SVM because it has pretty theoretical properties.  

This book is a good introductory material for kernel-based machine learning tools. The first part provides an reviews on the required mathematic tools in decision theory (risk and lost functions), statical learning theory and optimization theory. I strongly...  

This book is a good introductory material for kernel-based machine learning tools. The first part provides an reviews on the required mathematic tools in decision theory (risk and lost functions), statical learning theory and optimization theory. I strongly...  

Even it's been published for many years, the majority materials really provide a detail introduction of kernel methods........

Even it's been published for many years, the majority materials really provide a detail introduction of kernel methods........

用户评价

对于这个领域来说是经典。但是kernel这个领域本身属于歪门邪道

我觉得这本书的最大优势就是里面的notation都是数学家惯用的，看着太顺眼！再看看它的邻居TESL，里面的notation简直了！

我觉得这本书的最大优势就是里面的notation都是数学家惯用的，看着太顺眼！再看看它的邻居TESL，里面的notation简直了！

Everything about kernels, based on Smola's PhD thesis

好难，挑对自己（暂时）有用的部分读的。很喜欢书的排版，降低了不少难度（依然很难），没啥 pratical 的东西，感觉还得看论文。两个月的借书期到了，不好意思再拖着不还了……