Kernel based algorithms for mining huge data sets: supervised, semi-supervised, and unsupervised learning
Auteur :
Huang, Te-Ming
Éditeur :
Huang, Te-MingKecman, Vojislav,Kopriva, Ivica,
ISBN :
9783540316817
Date de publication :
2 mars 2006
Dimensions :
23,4 x 15,6 x 1,7 cm
Poids :
576 g
Format :
Laminated cover
Langue :
Anglais
Pays d'origine :
Allemagne
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.