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) - Grāmatas - Springer-Verlag Berlin and Heidelberg Gm - 9783540316817 - 2006. gada 2. marts
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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

Mediji Grāmatas     Hardcover Book   (Grāmata ar cieto muguriņu un vāku)
Izlaists 2006. gada 2. marts
ISBN13 9783540316817
Izdevēji Springer-Verlag Berlin and Heidelberg Gm
Lapas 260
Izmēri 156 × 234 × 17 mm   ·   576 g
Valoda Angļu  

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