Support vector machine software
Part 4. Bioinformatics
4.8. Modern Programming Paradigms in Biology
Basic Techniques and Approaches
Published Online: 15 JAN 2005
Copyright © 2005 John Wiley & Sons, Ltd
Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics
How to Cite
Noble, W. S. 2005. Support vector machine software. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 4:4.8:110.
- Published Online: 15 JAN 2005
The support vector machine has been used successfully to perform pattern recognition on many different types of biological data. However, applying the algorithm to a new problem domain is often nontrivial, because the algorithm offers many tunable parameters. Most important among these are the choice of the kernel function and the strength of the soft margin. This chapter describes the SVM algorithm and gives some practical advice for applying the algorithm to real biological data.
- support vector machine;
- pattern recognition;
- microarray analysis;
- machine learning