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Ensemble Learning: Pattern Classification Using Ensemble Methods - Second Edition

By: (Author) Lior Rokach

Extended Catalogue

Ksh 19,800.00

Format: Hardback or Cased Book

ISBN-10: 9811201951

ISBN-13: 9789811201950

Edition: Second Edition

Series: Series In Machine Perception And Artificial Intelligence

Publisher: World Scientific Publishing Co Pte Ltd

Imprint: World Scientific Publishing Co Pte Ltd

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Mar 25th, 2019

Print length: 300 Pages

Product Classification: Machine learning
Pattern recognition

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This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applications. More than a third of this edition comprised of new materials, highlighting descriptions of the classic methods, and extensions and novel approaches that have recently been introduced.Along with algorithmic descriptions of each method, the settings in which each method is applicable and the consequences and tradeoffs incurred by using the method is succinctly featured. R code for implementation of the algorithm is also emphasized.The unique volume provides researchers, students and practitioners in industry with a comprehensive, concise and convenient resource on ensemble learning methods.

This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applications. More than a third of this edition comprised of new materials, highlighting descriptions of the classic methods, and extensions and novel approaches that have recently been introduced.

Along with algorithmic descriptions of each method, the settings in which each method is applicable and the consequences and tradeoffs incurred by using the method is succinctly featured. R code for implementation of the algorithm is also emphasized.

The unique volume provides researchers, students and practitioners in industry with a comprehensive, concise and convenient resource on ensemble learning methods.


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