9781439830031

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

Zhou, Zhi-Hua

ISBN 10: 1439830037 / 1-4398-3003-7
ISBN 13: 9781439830031
Publisher: Chapman and Hall/CRC
Publication Date: 2012
Binding: Hardcover
Editorial Reviews for this title:
Synopsis:

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.


Editorial reviews may belong to another edition of this title.
 

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Ensemble Methods (ISBN: 9781439830031)
Zhou, Zhi-Hua
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Ensemble Methods: Foundations and Algorithms (Hardback) (ISBN: 9781439830031)
Zhou, Zhi-Hua
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Book Description: Taylor Francis Ltd, United States, 2012. Hardback. Book Condition: New. 235 x 156 mm. Language: English Brand New Book. 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. Bookseller Inventory # AAZ9781439830031

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Ensemble Methods: Foundations and Algorithms (Hardback) (ISBN: 9781439830031)
Zhou, Zhi-Hua
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Book Description: Taylor Francis Ltd, United States, 2012. Hardback. Book Condition: New. 235 x 156 mm. Brand New Book. 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. Bookseller Inventory # AAZ9781439830031

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Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Data Mining and Knowledge Discovery Serie) (ISBN: 9781439830031)
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Ensemble Methods: Foundations and Algorithms (Chapman & Hall/Crc Machine Learnig & Pattern Recognition) (ISBN: 1439830037 / 1-4398-3003-7)
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Book Description: Chapman and Hall/CRC. Hardcover. Book Condition: New. 1439830037 BRAND-NEW, Unread Copy in Perfect Condition. FAST FedEx shipping (you'll receive your order within 1-5 business days after shipping in most cases*), this helps to ensure your order arrives in perfect condition. PLEASE NOTE: FedEx does not generally deliver to PO Boxes or APO addresses, so please be sure to give us a physical street address to deliver to; also, unfortunately, we cannot ship this item to Alaska or Hawaii. THANKS! *(this applies to domestic shipments within the continental US - other destinations may take longer). Bookseller Inventory # TF9781439830031

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Ensemble Methods: Foundations and Algorithms (Hardcover) (ISBN: 1439830037 / 1-4398-3003-7)
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Book Description: 2012. Hardcover. Book Condition: New. 156mm x 236mm x. Hardcover. Shipping may be from our UK, US or Australian warehouse depending on stock availability. 222 pages. 0.502. Bookseller Inventory # 9781439830031

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