Kernel Based Algorithms for Mining Huge Data Sets

Kernel Based Algorithms for Mining Huge Data Sets
Author :
Publisher : Springer Science & Business Media
Total Pages : 266
Release :
ISBN-10 : 9783540316817
ISBN-13 : 3540316817
Rating : 4/5 (17 Downloads)

Book Synopsis Kernel Based Algorithms for Mining Huge Data Sets by : Te-Ming Huang

Download or read book Kernel Based Algorithms for Mining Huge Data Sets written by Te-Ming Huang and published by Springer Science & Business Media. This book was released on 2006-03-02 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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