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) - Knjige - Springer-Verlag Berlin and Heidelberg Gm - 9783642068560 - 25. novembra 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

Medij Knjige     Paperback Book   (Knjiga z mehkimi platnicami in lepljenim hrbtom)
Izdano 25. novembra 2010
ISBN13 9783642068560
Založniki Springer-Verlag Berlin and Heidelberg Gm
Strani 260
Dimenzije 156 × 234 × 14 mm   ·   394 g
Jezik Angleščina  

Več od istega **izdajatelja**

Ogled vseh Huang, Te-ming (The University of Auckland)