Ensembles Machine Learning Applications (29 results)
Ensembles in machine learning applications. Studies in computational intelligence; Vol. 373.
Okun, Oleg [Hrsg.], Giorgio [Hrsg.] Valentini and Matteo [Hrsg.] Re:
Language: English
Published by Berlin ; Heidelberg : Springer 2011
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
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OPp., gebundene Ausgabe. Condition: Befriedigend. XX, 252 S.: Ill., graph. Darst. ; 24 cm, Einband berieben. ISBN: 9783642229091 Sprache: Englisch Gewicht in Gramm: 680.
Ensembles in Machine Learning Applications
Okun, Oleg (EDT); Valentini, Giorgio (EDT); Re, Matteo (EDT)
Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
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Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Ensembles in Machine Learning Applications
Okun, Oleg (EDT); Valentini, Giorgio (EDT); Re, Matteo (EDT)
Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Ensembles in Machine Learning Applications
Okun, Oleg (EDT); Valentini, Giorgio (EDT); Re, Matteo (EDT)
Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Ensembles in Machine Learning Applications
Okun, Oleg (EDT); Valentini, Giorgio (EDT); Re, Matteo (EDT)
Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Language: English
Published by Springer-Verlag Berlin and Heidelberg GmbH and Co. KG, DE 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Paperback. Condition: New. Softcover reprint of the original 1st ed. 2011.
Language: English
Published by Springer 2011
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Hardcover
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Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Condition: New. pp. 272 Softcover reprint of the original 1st ed. 2011 edition NO-PA16APR2015-KAP.
Language: English
Published by Springer Berlin Heidelberg 2011
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Hardcover
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Gebunden. Condition: New.
Language: English
Published by Springer Berlin Heidelberg 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Ensembles in Machine Learning Applications
Okun, Oleg (Editor)/ Valentini, Giorgio (Editor)/ Re, Matteo (Editor)
Language: English
Published by Springer-Verlag New York Inc 2011
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Hardcover
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Hardcover. Condition: Brand New. 272 pages. 9.25x6.25x1.00 inches. In Stock.
Language: English
Published by J.B. Metzler 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Condition: Gut. Zustand: Gut | Seiten: 276 | Sprache: Englisch | Produktart: Bücher | This book contains the extended papers presented at the 3rd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA) that was held in conjunction with the European Conference on Machine Learning and Principles and… Practice of Knowledge Discovery in Databases (ECML/PKDD 2010, Barcelona, Catalonia, Spain). As its two predecessors, its main theme was ensembles of supervised and unsupervised algorithms ¿ advanced machinelearning and data mining technique. Unlike a single classification or clustering algorithm, an ensemble is a groupof algorithms, each of which first independently solves the task at hand by assigning a class or cluster label (voting) to instances in a dataset and after that all votes are combined together to produce the final class or cluster membership. As a result, ensembles often outperform best single algorithms in many real-world problems. This book consists of 14 chapters, each of which can be read independently of the others. In addition to two previous SUEMA editions, also published by Springer, many chapters in the current book include pseudo code and/or programming code of the algorithms described in them. This was done in order to facilitate ensemble adoption in practice and to help to both researchers and engineers developing ensemble applications.
More imagesLanguage: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Taschenbuch. Condition: Neu. Ensembles in Machine Learning Applications | Oleg Okun (u. a.) | Taschenbuch | Studies in Computational Intelligence | xx | Englisch | 2016 | Springer | EAN 9783662507063 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[d…ot]com | Anbieter: preigu.
Language: English
Published by Springer, Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book contains the extended papers presented at the 3rd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA) that was held in conjunction with the European Conference on Machine Learning and Principles and Pra…ctice of Knowledge Discovery in Databases (ECML/PKDD 2010, Barcelona, Catalonia, Spain). As its two predecessors, its main theme was ensembles of supervised and unsupervised algorithms - advanced machinelearning and data mining technique. Unlike a single classification or clustering algorithm, an ensemble is a groupof algorithms, each of which first independently solves the task at hand by assigning a class or cluster label (voting) to instances in a dataset and after that all votes are combined together to produce the final class or cluster membership. As a result, ensembles often outperform best single algorithms in many real-world problems. This book consists of 14 chapters, each of which can be read independently of the others. In addition to two previous SUEMA editions, also published by Springer, many chapters in the current book include pseudo code and/or programming code of the algorithms described in them. This was done in order to facilitate ensemble adoption in practice and to help to both researchers and engineers developing ensemble applications.
Language: English
Published by Springer Berlin Heidelberg 2011
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book contains the extended papers presented at the 3rd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA) that was held in conjunction with the European Conference on Machine Learning and Principles and Practice o…f Knowledge Discovery in Databases (ECML/PKDD 2010, Barcelona, Catalonia, Spain). As its two predecessors, its main theme was ensembles of supervised and unsupervised algorithms - advanced machinelearning and data mining technique. Unlike a single classification or clustering algorithm, an ensemble is a groupof algorithms, each of which first independently solves the task at hand by assigning a class or cluster label (voting) to instances in a dataset and after that all votes are combined together to produce the final class or cluster membership. As a result, ensembles often outperform best single algorithms in many real-world problems. This book consists of 14 chapters, each of which can be read independently of the others. In addition to two previous SUEMA editions, also published by Springer, many chapters in the current book include pseudo code and/or programming code of the algorithms described in them. This was done in order to facilitate ensemble adoption in practice and to help to both researchers and engineers developing ensemble applications.
Language: English
Published by Springer 2011
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Hardcover
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 272 | Sprache: Englisch | Produktart: Bücher | This book contains the extended papers presented at the 3rd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA) that was held in conjunction with the European Conference on Machine Learning and Prin…ciples and Practice of Knowledge Discovery in Databases (ECML/PKDD 2010, Barcelona, Catalonia, Spain). As its two predecessors, its main theme was ensembles of supervised and unsupervised algorithms ¿ advanced machinelearning and data mining technique. Unlike a single classification or clustering algorithm, an ensemble is a groupof algorithms, each of which first independently solves the task at hand by assigning a class or cluster label (voting) to instances in a dataset and after that all votes are combined together to produce the final class or cluster membership. As a result, ensembles often outperform best single algorithms in many real-world problems. This book consists of 14 chapters, each of which can be read independently of the others. In addition to two previous SUEMA editions, also published by Springer, many chapters in the current book include pseudo code and/or programming code of the algorithms described in them. This was done in order to facilitate ensemble adoption in practice and to help to both researchers and engineers developing ensemble applications.
Language: English
Published by Springer-Verlag Berlin and Heidelberg GmbH and Co. KG, DE 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Paperback. Condition: New. Softcover reprint of the original 1st ed. 2011.
Language: English
Published by Springer 2011
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Hardcover
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Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Ensembles in Machine Learning Applications (Studies in Computational Intelligence)
Okun, Oleg (Editor) / Re, Matteo (Editor) / Valentini, Giorgio (Editor)
Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
- Print on Demand
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Paperback. Condition: Brand New. reprint edition. 252 pages. 9.25x6.10x0.65 inches. In Stock. This item is printed on demand.
Language: English
Published by Springer Berlin Heidelberg Aug 2016 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book contains the extended papers presented at the 3rd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA) that was held in conjunction with the European Conference on Machine Learning and Pr…inciples and Practice of Knowledge Discovery in Databases (ECML/PKDD 2010, Barcelona, Catalonia, Spain). As its two predecessors, its main theme was ensembles of supervised and unsupervised algorithms - advanced machinelearning and data mining technique. Unlike a single classification or clustering algorithm, an ensemble is a groupof algorithms, each of which first independently solves the task at hand by assigning a class or cluster label (voting) to instances in a dataset and after that all votes are combined together to produce the final class or cluster membership. As a result, ensembles often outperform best single algorithms in many real-world problems. This book consists of 14 chapters, each of which can be read independently of the others. In addition to two previous SUEMA editions, also published by Springer, many chapters in the current book include pseudo code and/or programming code of the algorithms described in them. This was done in order to facilitate ensemble adoption in practice and to help to both researchers and engineers developing ensemble applications. 276 pp. Englisch.
Language: English
Published by Springer Berlin Heidelberg Sep 2011 2011
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Hardcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book contains the extended papers presented at the 3rd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA) that was held in conjunction with the European Conference on Machine Learning and Principle…s and Practice of Knowledge Discovery in Databases (ECML/PKDD 2010, Barcelona, Catalonia, Spain). As its two predecessors, its main theme was ensembles of supervised and unsupervised algorithms - advanced machinelearning and data mining technique. Unlike a single classification or clustering algorithm, an ensemble is a groupof algorithms, each of which first independently solves the task at hand by assigning a class or cluster label (voting) to instances in a dataset and after that all votes are combined together to produce the final class or cluster membership. As a result, ensembles often outperform best single algorithms in many real-world problems. This book consists of 14 chapters, each of which can be read independently of the others. In addition to two previous SUEMA editions, also published by Springer, many chapters in the current book include pseudo code and/or programming code of the algorithms described in them. This was done in order to facilitate ensemble adoption in practice and to help to both researchers and engineers developing ensemble applications. 272 pp. Englisch.
Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
- Print on Demand
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Condition: New. Print on Demand pp. 272.
Language: English
Published by Springer 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
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Condition: New. PRINT ON DEMAND pp. 272.
Language: English
Published by Springer, Springer Aug 2016 2016
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Softcover
- Print on Demand
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book contains the extended papers presented at the 3rd Workshop on Supervised and Unsupervised Ensemble Methodsand their Applications (SUEMA) that was held in conjunction with the European Conference on Machine Learning andPrincipl…es and Practice of Knowledge Discovery in Databases (ECML/PKDD 2010, Barcelona, Catalonia, Spain).As its two predecessors, its main theme was ensembles of supervised and unsupervised algorithms ¿ advanced machinelearning and data mining technique. Unlike a single classification or clustering algorithm, an ensemble is a groupof algorithms, each of which first independently solves the task at hand by assigning a class or cluster label(voting) to instances in a dataset and after that all votes are combined together to produce the final class orcluster membership. As a result, ensembles often outperform best single algorithms in many real-world problems.This book consists of 14 chapters, each of which can be read independently of the others. In addition to twoprevious SUEMA editions, also published by Springer, many chapters in the current book include pseudo code and/orprogramming code of the algorithms described in them. This was done in order to facilitate ensemble adoption inpractice and to help to both researchers and engineers developing ensemble applications.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 276 pp. Englisch.
Language: English
Published by Springer, Springer Sep 2011 2011
Series: Studies in Computational Intelligence, Book 28 of 538. Book 28 of 538 - Studies in Computational Intelligence
- Hardcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, Germanybuchversandmimpf2000
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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book contains the extended papers presented at the 3rd Workshop on Supervised and Unsupervised Ensemble Methodsand their Applications (SUEMA) that was held in conjunction with the European Conference on Machine Learning andPrinciples and…Practice of Knowledge Discovery in Databases (ECML/PKDD 2010, Barcelona, Catalonia, Spain).As its two predecessors, its main theme was ensembles of supervised and unsupervised algorithms ¿ advanced machinelearning and data mining technique. Unlike a single classification or clustering algorithm, an ensemble is a groupof algorithms, each of which first independently solves the task at hand by assigning a class or cluster label(voting) to instances in a dataset and after that all votes are combined together to produce the final class orcluster membership. As a result, ensembles often outperform best single algorithms in many real-world problems.This book consists of 14 chapters, each of which can be read independently of the others. In addition to twoprevious SUEMA editions, also published by Springer, many chapters in the current book include pseudo code and/orprogramming code of the algorithms described in them. This was done in order to facilitate ensemble adoption inpractice and to help to both researchers and engineers developing ensemble applications.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 272 pp. Englisch.
