Ontology type: schema:Chapter Open Access: True
2009-10-30
AUTHORS ABSTRACTThe Support Vector Machine (SVM) is a widely used classifier in bioinformatics. Obtaining the best results with SVMs requires an understanding of their workings and the various ways a user can influence their accuracy. We provide the user with a basic understanding of the theory behind SVMs and focus on their use in practice. We describe the effect of the SVM parameters on the resulting classifier, how to select good values for those parameters, data normalization, factors that affect training time, and software for training SVMs. More... »
PAGES223-239
Data Mining Techniques for the Life Sciences
ISBN
978-1-60327-240-7
978-1-60327-241-4
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DOIhttp://dx.doi.org/10.1007/978-1-60327-241-4_13
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PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/20221922
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