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Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-Supervised, and Unsupervised Learning PDF

266 Pages·2006·5.2 MB·English
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by Te-Ming Huang| 2006| 266 pages| 5.2| English

About Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-Supervised, and Unsupervised Learning

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.

Detailed Information

Author:Te-Ming Huang
Publication Year:2006
ISBN:9783540316817
Pages:266
Language:English
File Size:5.2
Format:PDF
Price:FREE
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