Kernel Based Algorithms for Mining Huge Data Sets : Supervised, Semi-supervis...
Kernel Based Algorithms for Mining Huge Data Sets : Supervised, Semi-supervised, And Unsupervised Learning, Hardcover by Huang, Te-ming; Kecman, Vojislav; Kopriva, Ivica, ISBN 3540316817, ISBN-13 9783540316817, Like New Used, Free shipping in the US This is the first book treating the fields of supervised, semi-supervised and unsupervised machine learning collectively. Th 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.
Specifications
| ISBN | 9783540316817 |
| Item Length | 9.3 in |
| Publication Year | 2006 |
| Type | Textbook |
| Format | Hardcover |
| Language | English |
| Item Weight | 44.8 Oz |
| Item Width | 6.1 in |
| Number Of Pages | Xvi, 260 Pages |
A nice touch in this textbook is the checklist of learning outcomes at the start.
