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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) 1997 edition
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También disponible como:
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)
Presents both the theory and the algorithms for mining huge data sets using support vector machines (SVMs) in an iterative way. This book 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
| Medios de comunicación | Libros Hardcover Book (Libro con lomo y cubierta duros) |
| Publicado | 2 de marzo de 2006 |
| ISBN13 | 9783540316817 |
| Editores | Springer-Verlag Berlin and Heidelberg Gm |
| Páginas | 260 |
| Dimensiones | 156 × 234 × 17 mm · 576 g |
| Lengua | Inglés |