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) - Bøker - Springer-Verlag Berlin and Heidelberg Gm - 9783540316817 - 2. mars 2006
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Huang, Te-ming (The University of Auckland)
Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning - Studies in Computational Intelligence 1997 edition

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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

Media Bøker     Innbunden bok   (Bok med hard rygg og stivt omslag)
Utgitt 2. mars 2006
ISBN13 9783540316817
Utgivere Springer-Verlag Berlin and Heidelberg Gm
Antall sider 260
Mål 156 × 234 × 17 mm   ·   576 g
Språk Engelsk  

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