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Kernel Methods for Pattern Analysis
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Binding: Hardcover
Dewey Decimal Number: 006.31
EAN: 9780521813976
ISBN: 0521813972
Label: Cambridge University Press
Manufacturer: Cambridge University Press
Number Of Items: 1
Number Of Pages: 476
Publication Date: June 28, 2004
Publisher: Cambridge University Press
Studio: Cambridge University Press
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Editorial Review:
This book provides professionals with a large selection of algorithms, kernels and solutions ready for implementation and suitable for standard pattern discovery problems in fields such as bioinformatics, text analysis and image analysis. It also serves as an introduction for students and researchers to the growing field of kernel-based pattern analysis, demonstrating with examples how to handcraft an algorithm or a kernel for a new specific application, and covering all the necessary conceptual and mathematical tools to do so.
This book fulfils two major roles: firstly it provides practitioners with a large toolkit of algorithms, kernels and solutions ready to be implemented, suitable for standard pattern discovery problems in field such as bioinformatics, text analysis, image analysis. Secondly it provides an easy introduction for students and researchers to the growing field of kernel-based pattern analysis, demonstrating with examples how to handcraft an algorithm or a kernel for a new specific application, and covering all the necessary conceptual and mathematical tools to do so.
Customer Reviews
Average Rating: 
Rating:  - Quite Useful
A very useful book and quite a nice read. I bought the book after reading a few chapters. Even now, an year after my grad school, I still read this. A good reference.
Nice print, no mistakes, MATLAB code. You get everything on Kernel Methods, from theory to implementation. A perfect book and helped me a lot in my research.
Rating:  - Sloppy
Sloppy language, sloppy definitions, sloppy proofs.
Constant repetitions do not add any clarity either.
Rating:  - Nice introduction, but no more
Well, at first I was petrified to find a book that sounded like it deeply explores the subject of kernel methods. But all in all, it did not quite achieve what I hoped for. As a practical approach, when it comes to implementation, it serves nicely as a reference. The deeper mathematical roots of kernels (especially when it comes to measure theory and functional analysis) are not dealt with at all or just scratched at the very surface. The notation is sometimes awkward, mentioning for example the ... Read More
Rating: - coherent and accessible reference, ready-to-use algorithms
This work presents a coherent overview of an important field in machine learning. The unifying framework of kernel methods has proven state of the art results and the community has been waiting for a book like this to make both theory and practice of kernel methods accesssible for readers of all different backgrounds (researchers, students, practioners from both academia and industry, ...).
It is theoretically well-founded, the resulting algorithms are well-explained and made accessible ... Read More
Rating: - A Useful Reference on Kernel Methods
The book is divided into 3 parts. The theory is all in part I,
the rest of the book is a cook-book with plenty of matlab code.
The website contains most of the same code + data online. Readable, complete.
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