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Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning - Studies in Computational Intelligence Huang, Te-ming (The University of Auckland) 1st Ed. Softcover of Orig. Ed. 2006 edition
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Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning - Studies in Computational Intelligence
Huang, Te-ming (The University of Auckland)
This is the first book treating the fields of supervised, semi-supervised and unsupervised machine learning collectively. The book presents both the theory and the algorithms for mining huge data sets using support vector machines (SVMs) in an iterative way. It demonstrates how kernel based SVMs can be used for dimensionality reduction and shows the similarities and differences between the two most popular unsupervised techniques.
260 pages, 19 black & white tables, biography
| Media | Boeken Paperback Book (Boek met zachte kaft en gelijmde rug) |
| Vrijgegeven | 25 november 2010 |
| ISBN13 | 9783642068560 |
| Uitgevers | Springer-Verlag Berlin and Heidelberg Gm |
| Pagina's | 260 |
| Afmetingen | 156 × 234 × 14 mm · 394 g |
| Taal en grammatica | Engels |
Bekijk alles van Huang, Te-ming (The University of Auckland) ( bijv. Hardcover Book en Paperback Book )