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) - Books - Springer-Verlag Berlin and Heidelberg Gm - 9783540316817 - March 2, 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 Books     Hardcover Book   (Book with hard spine and cover)
Released March 2, 2006
ISBN13 9783540316817
Publishers Springer-Verlag Berlin and Heidelberg Gm
Pages 260
Dimensions 156 × 234 × 17 mm   ·   576 g
Language English  

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