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 - 9783642068560 - 25. november 2010
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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 1st Ed. Softcover of Orig. Ed. 2006 edition

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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 Bøker     Pocketbok   (Bok med mykt omslag og limt rygg)
Utgitt 25. november 2010
ISBN13 9783642068560
Utgivere Springer-Verlag Berlin and Heidelberg Gm
Antall sider 260
Mål 156 × 234 × 14 mm   ·   394 g
Språk Engelsk  

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