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Ensemble Methods: Foundations and Algorithms
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Ensemble Methods: Foundations and Algorithms Hardback - 2012 - 1st Edition

by Zhi-Hua Zhou

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Reader reviews for Ensemble Methods: Foundations and Algorithms

From the publisher

An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field.

After presenting background and terminology, the book covers the main algorithms and theories, including Boosting, Bagging, Random Forest, averaging and voting schemes, the Stacking method, mixture of experts, and diversity measures. It also discusses multiclass extension, noise tolerance, error-ambiguity and bias-variance decompositions, and recent progress in information theoretic diversity.

Moving on to more advanced topics, the author explains how to achieve better performance through ensemble pruning and how to generate better clustering results by combining multiple clusterings. In addition, he describes developments of ensemble methods in semi-supervised learning, active learning, cost-sensitive learning, class-imbalance learning, and comprehensibility enhancement.

Details

  • Title Ensemble Methods: Foundations and Algorithms
  • Author Zhi-Hua Zhou
  • Binding Hardback
  • Edition number 1st
  • Edition 1
  • Pages 236
  • Volumes 1
  • Language ENG
  • Publisher CRC Press
  • Publication date 2012-06-06
  • Illustrated Yes
  • ISBN 9781439830031 / 1439830037
  • Weight 1.13 lbs (0.51 kg)
  • Dimensions 9.21 x 6.14 x 0.56 in (23.39 x 15.60 x 1.42 cm)
  • Category Computers - Data Base Management
  • Library of Congress subjects Set theory, Mathematical analysis
  • Library of Congress Catalogue Number 2012014555
  • Dewey Decimal Code 006.31

About the author

Zhi-Hua Zhou is a professor in the Department of Computer Science and Technology and the National Key Laboratory for Novel Software Technology at Nanjing University. Dr. Zhou is the founding steering committee co-chair of ACML and associate editor-in-chief, associate editor, and editorial board member of numerous journals. He has published extensively in top-tier journals, chaired many conferences, and won six international journal/conference/competition awards. His research interests encompass the areas of machine learning, data mining, pattern recognition, and multimedia information retrieval.

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Ensemble Methods : Foundations and Algorithms

Ensemble Methods : Foundations and Algorithms

by Zhi-Hua Zhou

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CRC Press LLC, 2012. Hardcover. Very Good. Disclaimer:A copy that has been read, but remains in excellent condition. Pages are intact and are not marred by notes or highlighting, but may contain a neat previous owner name. The spine remains undamaged. At ThriftBooks, our motto is: Read More, Spend Less.Dust jacket quality is not guaranteed.
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Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Machine Learning &...
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Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

by Zhou, Zhi-Hua

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Ensemble Methods (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
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Ensemble Methods (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

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Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Machine Learning &...
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Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

by Zhou, Zhi-Hua

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Ensemble Methods: Foundations and Algorithms (Chapman & Hall/Crc Machine Learnig &...
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Ensemble Methods: Foundations and Algorithms (Chapman & Hall/Crc Machine Learnig & Pattern Recognition)

by Zhi-Hua Zhou

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Ensemble Methods: Foundations and Algorithms (Chapman & Hall/Crc Machine Learnig &...
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Ensemble Methods: Foundations and Algorithms (Chapman & Hall/Crc Machine Learnig & Pattern Recognition)

by Zhi-Hua Zhou

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