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Kernel Based Algorithms For Mining Huge Data Sets eBook

Supervised, Semi-Supervised, And Unsupervised Learning

by Vojislav Kecman, Te-Ming Huang e Ivica Kopriva
language: english
Publisher: Springer Berlin Heidelberg, May of 2006 ‧
118,59€
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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.

Kernel Based Algorithms For Mining Huge Data Sets

Supervised, Semi-Supervised, And Unsupervised Learning

by Vojislav Kecman, Te-Ming Huang e Ivica Kopriva

Property Description
ISBN: 9783540316893
Publisher: Springer Berlin Heidelberg
Release Date: May of 2006
Language: English
Format: eBook
File Format and Compatibility: PDF para ADE
Collection: Studies In Computational Intelligence
Categories: eBooks in English > Science > Mathematics
eBooks in English > Computing > Database
EAN: 9783540316893

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