A Gentle Introduction to Support Vector Machines in Biomedicine: Theory and methods

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World Scientific, 2011 - Computers - 183 pages
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Support Vector Machines (SVMs) are among the most important recent developments in pattern recognition and statistical machine learning. They have found a great range of applications in various fields including biology and medicine. However, biomedical researchers often experience difficulties grasping both the theory and applications of these important methods because of lack of technical background. The purpose of this book is to introduce SVMs and their extensions and allow biomedical researchers to understand and apply them in real-life research in a very easy manner. The book is to consist of two volumes: theory and methods (Volume 1) and cases studies (Volume 2).The proposed book follows the approach of “programmed learning” whereby material is presented in short sections called “frames”. Each frame consists of a very small amount of information to be learned, a multiple choice quiz, and answers to the quiz. The reader can proceed to the next frame only after verifying the correct answers to the current frame.
 

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Contents

1 Introduction
1
2 Necessary Mathematical Concepts
19
Classical Formulation
40
4 Basic Principles of Statistical Machine Learning
64
5 Model Selection for SVMs
73
6 SVMs for MultiCategory Classification
91
7 Support Vector Regression SVR
97
8 Novelty Detection with SVMBased Methods
119
9 Support Vector Clustering Contributed by Nikita I Lytkin
136
10 SVMBased Variable Selection
154
11 Computing Posterior Class Probabilities for SVM Classifiers
168
12 Conclusions
174
Appendix
176
Bibliography
178
Index
181
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