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Anglický jazyk
Kernel Based Algorithms for Mining Huge Data Sets
Autor: Te-Ming Huang
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... Viac o knihe
Na objednávku
98.99 €
bežná cena: 109.99 €
O knihe
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.
- Vydavateľstvo: Springer Berlin Heidelberg
- Rok vydania: 2006
- Formát: Hardback
- Rozmer: 241 x 160 mm
- Jazyk: Anglický jazyk
- ISBN: 9783540316817
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