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Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning by Te-Ming Huang 9783642068560

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9783642068560
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9783642068560
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Description

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.

Book Information
ISBN 9783642068560
Author Te-Ming Huang
Format Paperback
Page Count 260
Imprint Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Publisher Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Weight(grams) 724g

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