Abstract
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for high-dimensional sparse data commonly encountered in applications like text classification, word-sense disambiguation, and drug design. These applications involve a large number of examples n as well as a large number of features N, while each example has only s
Keywords
Support vector machineComputer scienceArtificial intelligenceMachine learningWord (group theory)Training setWord-sense disambiguationPattern recognition (psychology)MathematicsWordNet
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Publication Info
- Year
- 2006
- Type
- article
- Citations
- 1944
- Access
- Closed
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Cite This
Thorsten Joachims
(2006).
Training linear SVMs in linear time.
.
https://doi.org/10.1145/1150402.1150429
Identifiers
- DOI
- 10.1145/1150402.1150429