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Machine Learning : An Introduction To Supervised And Unsupervised Learning Algorithms
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Springer
Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-Supervised, and Unsupervised Learning
Product Code:
9783540316817
ISBN13:
9783540316817
Condition:
New
$118.37
Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-Supervised, and Unsupervised Learning
$118.37
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.
| Author: Te-Ming Huang |
| Publisher: Springer |
| Publication Date: Mar 02, 2006 |
| Number of Pages: 260 pages |
| Binding: Hardback or Cased Book |
| ISBN-10: 3540316817 |
| ISBN-13: 9783540316817 |
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