A User’s Guide to Support Vector Machines View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2009-10-30

AUTHORS

Asa Ben-Hur , Jason Weston

ABSTRACT

The 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... »

PAGES

223-239

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-60327-241-4_13

DOI

http://dx.doi.org/10.1007/978-1-60327-241-4_13

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1042784786

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20221922


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