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Supervised and Unsupervised Ensemble Methods and Their Applications
Language: English
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 2008
ISBN 10: 3540789804 ISBN 13: 9783540789802
Hardcover. Condition: Très bon. Ancien livre de bibliothèque. Salissures sur la tranche. Edition 2008. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Stains on the edge. Edition 2008. Ammareal gives back up to 15% of this item's net price to charity organizations.
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
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Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
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Condition: New. pp. 196.
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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US$ 108.20
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Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketCondition: New. pp. 196 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.
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Supervised and Unsupervised Ensemble Methods and their Applications (Paperback)
Language: English
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2010
ISBN 10: 3642097766 ISBN 13: 9783642097768
First Edition
Paperback. Condition: new. Paperback. The rapidly growing amount of data, available from di?erent technologies in the ?eld of bio-sciences, high-energy physics, economy, climate analysis, and in several other scienti?c disciplines, requires a new generation of machine learning and statistical methods to deal with their complexity and hete- geneity. As data collections becomes easier, data analysis is required to be more sophisticated in order to extract useful information from the available data. Even if data can be represented in several ways, according to their structural characteristics, ranging from strings, lists, trees to graphs and other more complex data structures, in most applications they are typically represented as a matrix whose rows correspond to measurable characteristics called f- tures, attributes, variables, depending on the considered discipline and whose columns correspond to examples (cases, samples, patterns). In order to avoid confusion,we will talk about features and examples.In real-worldtasks,there canbe manymorefeatures than examples(cancer classi?cationbasedongene expressionlevels in bioinformatics) or there can be many more examples than features(intrusion detection in computer/networksecurity).In addition, each example can be either labeled or not. Attaching labels allows to distinguish members of the same class or group from members of other classes or groups. Hence, one can talk about supervised and unsupervised tasks that can be solved by machine learning methods. Since it is widely accepted that no single classi?er or clustering algorithm canbesuperiortotheothers,ensemblesofsupervisedandunsupervisedme- ods are gaining popularity. A typical ensemble includes a number of clas- ?ers/clustererswhosepredictionsarecombinedtogetheraccordingtoacertain rule, e.g. majority vote. This book results from the workshop on Supervised and Unsupervised Ensemble Methods and their Applications (briefly, SUEMA) in June 2007 in Girona, Spain. This workshop was held alongside the 3rd Iberian Conference on Pattern Recognition and Image Analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Condition: New.
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Applications of Supervised and Unsupervised Ensemble Methods (Paperback)
Language: English
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2012
ISBN 10: 3642260772 ISBN 13: 9783642260773
Paperback. Condition: new. Paperback. This book contains the extended papers presented at the 2nd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA)heldon21-22July,2008inPatras,Greece,inconjunctionwiththe 18thEuropeanConferenceon Arti?cial Intelligence(ECAI 2008). This wo- shop was a successor of the smaller event held in 2007 in conjunction with 3rd Iberian Conference on Pattern Recognition and Image Analysis, Girona, Spain. The success of that event as well as the publication of workshop - pers in the edited book "Supervised and Unsupervised Ensemble Methods and their Applications", published by Springer-Verlag in Studies in Com- tational Intelligence Series in volume 126, encouraged us to continue a good tradition. The scope of both SUEMA workshops (hence, the book as well) is the application of theoretical ideas in the ?eld of ensembles of classi?cation and clusteringalgorithmstoreal/lifeproblemsinscienceandindustry. Ensembles, which represent a number of algorithms whose class or cluster membership predictions are combined together to produce a single outcome value, have alreadyprovedto be a viable alternativeto a single best algorithmin various practical tasks under di?erent scenarios, from bioinformatics to biometrics, from medicine to network security.The ensemble approach is caused to life by the famous "no free lunch" theorem, stating that there is no absolutely best algorithm to solve all problems. Although ensembles cannot be cons- ered as absolute remedy of a single algorithm de?ciency, it is widely believed thatensemblesprovideabetteranswerto"nofreelunch"theoremthanas- glebestalgorithm. Statistical,algorithmical,representational,computational and practical reasons can explain the success of ensemble methods. Expanding upon presentations at last year's SUEMA (Supervised and Unsupervised Ensemble Methods and Applications) meeting, this volume explores recent developments in the field. Useful examples act as a guide for practitioners in computational intelligence. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Condition: New.
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Condition: New. pp. 196.
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Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
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Applications of Supervised and Unsupervised Ensemble Methods (Hardcover)
Language: English
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2009
ISBN 10: 3642039987 ISBN 13: 9783642039980
Hardcover. Condition: new. Hardcover. This book contains the extended papers presented at the 2nd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA)heldon21-22July,2008inPatras,Greece,inconjunctionwiththe 18thEuropeanConferenceon Arti?cial Intelligence(ECAI 2008). This wo- shop was a successor of the smaller event held in 2007 in conjunction with 3rd Iberian Conference on Pattern Recognition and Image Analysis, Girona, Spain. The success of that event as well as the publication of workshop - pers in the edited book "Supervised and Unsupervised Ensemble Methods and their Applications", published by Springer-Verlag in Studies in Com- tational Intelligence Series in volume 126, encouraged us to continue a good tradition. The scope of both SUEMA workshops (hence, the book as well) is the application of theoretical ideas in the ?eld of ensembles of classi?cation and clusteringalgorithmstoreal/lifeproblemsinscienceandindustry. Ensembles, which represent a number of algorithms whose class or cluster membership predictions are combined together to produce a single outcome value, have alreadyprovedto be a viable alternativeto a single best algorithmin various practical tasks under di?erent scenarios, from bioinformatics to biometrics, from medicine to network security.The ensemble approach is caused to life by the famous "no free lunch" theorem, stating that there is no absolutely best algorithm to solve all problems. Although ensembles cannot be cons- ered as absolute remedy of a single algorithm de?ciency, it is widely believed thatensemblesprovideabetteranswerto"nofreelunch"theoremthanas- glebestalgorithm. Statistical,algorithmical,representational,computational and practical reasons can explain the success of ensemble methods. Expanding upon presentations at last year's SUEMA (Supervised and Unsupervised Ensemble Methods and Applications) meeting, this volume explores recent developments in the field. Useful examples act as a guide for practitioners in computational intelligence. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | majority vote.
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Supervised and Unsupervised Ensemble Methods and their Applications (Hardcover)
Language: English
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2008
ISBN 10: 3540789804 ISBN 13: 9783540789802
Hardcover. Condition: new. Hardcover. The rapidly growing amount of data, available from di?erent technologies in the ?eld of bio-sciences, high-energy physics, economy, climate analysis, and in several other scienti?c disciplines, requires a new generation of machine learning and statistical methods to deal with their complexity and hete- geneity. As data collections becomes easier, data analysis is required to be more sophisticated in order to extract useful information from the available data. Even if data can be represented in several ways, according to their structural characteristics, ranging from strings, lists, trees to graphs and other more complex data structures, in most applications they are typically represented as a matrix whose rows correspond to measurable characteristics called f- tures, attributes, variables, depending on the considered discipline and whose columns correspond to examples (cases, samples, patterns). In order to avoid confusion,we will talk about features and examples.In real-worldtasks,there canbe manymorefeatures than examples(cancer classi?cationbasedongene expressionlevels in bioinformatics) or there can be many more examples than features(intrusion detection in computer/networksecurity).In addition, each example can be either labeled or not. Attaching labels allows to distinguish members of the same class or group from members of other classes or groups. Hence, one can talk about supervised and unsupervised tasks that can be solved by machine learning methods. Since it is widely accepted that no single classi?er or clustering algorithm canbesuperiortotheothers,ensemblesofsupervisedandunsupervisedme- ods are gaining popularity. A typical ensemble includes a number of clas- ?ers/clustererswhosepredictionsarecombinedtogetheraccordingtoacertain rule, e.g. majority vote. This book results from the workshop on Supervised and Unsupervised Ensemble Methods and their Applications (briefly, SUEMA) in June 2007 in Girona, Spain. This workshop was held alongside the 3rd Iberian Conference on Pattern Recognition and Image Analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Applications of Supervised and Unsupervised Ensemble Methods (Studies in Computational Intelligence, 245)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 132.96
US$ 16.40 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Supervised and Unsupervised Ensemble Methods and their Applications (Studies in Computational Intelligence, 126)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 132.96
US$ 16.40 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Condition: New. pp. 196.
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Condition: New. pp. 292.
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US$ 175.92
US$ 13.69 shipping
Ships from United Kingdom to U.S.A.Quantity: 2 available
Add to basketPaperback. Condition: Brand New. 2010 edition. 288 pages. 9.25x6.10x0.69 inches. In Stock.
