1. Support vector machines
- Author
-
Hearst, Marti A.
- Subjects
Machine learning -- Usage ,Intelligent devices -- Usage ,Artificial intelligence -- Usage ,Business ,Computers ,Computers and office automation industries ,Electronics - Abstract
Support vector machines (SVMs) provide a significant algorithm for machine learning that can lead to high performances in a wide range of practical applications. SVMs are better than other machine learning algorithms because they can be analyzed theoretically using simple ideas from computational learning theory. Examples of real problems that can be addressed by SVMs include text categorization and face detection. The algorithm can be implemented efficiently using sequential minimal optimization. more...
- Published
- 1998