Kernel Based Algorithms for Mining Huge Data Sets (Studies in Computational Intelligence, #17)

by Te-Ming Huang, Vojislav Kecman, and Ivica Kopriva

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Book cover for Kernel Based Algorithms for Mining Huge Data Sets

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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.

  • ISBN10 3540819975
  • ISBN13 9783540819974
  • Publish Date 31 August 2008 (first published 2 March 2006)
  • Publish Status Withdrawn
  • Out of Print 18 October 2014
  • Publish Country US
  • Imprint Springer
  • Format Paperback (US Trade)
  • Pages 280
  • Language English