DocumentCode :
983622
Title :
Learning Kernel Classifiers: Theory and Algorithms (Herbrich, R.; 2002) [Book reviews]
Author :
Angulo, Cecilio
Volume :
19
Issue :
11
fYear :
2008
Firstpage :
1990
Lastpage :
1990
Abstract :
Focusing on classification learning, this book covers learning algorithms and learning theory. The book concludes with appendices covering some of the technical aspects involved. The book is a good reference for scientists and engineers interested in learning about kernel classifiers. It is not very suitable as a primary student text, but is recommended as secondary reading for students requiring an in-depth insight into this area.
Keywords :
Bayesian methods; Book reviews; Kernel; Machine learning; Machine learning algorithms; Statistical learning; Stochastic processes; Support vector machine classification; Support vector machines; Virtual colonoscopy;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/TNN.2008.2008390
Filename :
4668660
Link To Document :
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