Ensemble Machine Learning: Methods and Applications - Couverture souple

9781489988171: Ensemble Machine Learning: Methods and Applications

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ISBN 10 : 1489988173 ISBN 13 : 9781489988171

Editeur : Springer, 2014

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It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics.

Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.

Les informations fournies dans la section � Synopsis � peuvent faire r�f�rence � une autre �dition de ce titre.

� propos de l?auteur

Dr. Zhang works for Microsoft. Dr. Ma works for Honeywell.

Les informations fournies dans la section � A propos du livre � peuvent faire r�f�rence � une autre �dition de ce titre.

�diteur: Springer
Date d'�dition: 2014
Langue: anglais
ISBN 10: 1489988173
ISBN 13: 9781489988171
Reliure: Broch�
Nombre de pages: 340
�diteur: Zhang Cha, Ma Yunqian
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ISBN 10 : 1441993258 ISBN 13 : 9781441993250
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Ensemble Machine Learning

Yunqian Ma

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ISBN 10 : 1489988173 ISBN 13 : 9781489988171

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed 'ensemble learning' by researchers in computational intelligence and machine learning, it is known to improve a decision system's robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as 'boosting' and 'random forest' facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike. 340 pp. Englisch. N� de r�f. du vendeur 9781489988171

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Ensemble Machine Learning

Zhang, Cha|Ma, Yunqian

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers all existing methods developed for ensemble learningPresents overview and in-depth knowledge about ensemble learningDiscusses the pros and cons of various ensemble learning methodsDemonstrate how ensemble learning can be used . N� de r�f. du vendeur 4212968

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Ensemble Machine Learning : Methods and Applications

Yunqian Ma

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ISBN 10 : 1489988173 ISBN 13 : 9781489988171

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed 'ensemble learning' by researchers in computational intelligence and machine learning, it is known to improve a decision system's robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as 'boosting' and 'random forest' facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike. N� de r�f. du vendeur 9781489988171

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Ensemble Machine Learning

Yunqian Ma

Edit� par Springer New York, Springer US Apr 2014, 2014

ISBN 10 : 1489988173 ISBN 13 : 9781489988171

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed �ensemble learning� by researchers in computational intelligence and machine learning, it is known to improve a decision system�s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as �boosting� and �random forest� facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics.Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 340 pp. Englisch. N� de r�f. du vendeur 9781489988171

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