Lingua: Inglese
Editore: Cham, Springer International Publishing., 2014
ISBN 10: 331906598X ISBN 13: 9783319065984
Da: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germania
EUR 14,00
Quantità: 2 disponibili
Aggiungi al carrelloAufl. 2014. XII, 103 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stamped. Studies in Big Data ; 6. Sprache: Englisch.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 113,49
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 115,23
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Da: Chiron Media, Wallingford, Regno Unito
EUR 112,33
Quantità: 10 disponibili
Aggiungi al carrelloPF. Condizione: New.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 130,59
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 115,22
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Aggiungi al carrelloCondizione: New.
Condizione: New. pp. xii + 105.
Condizione: New. pp. 105.
Lingua: Inglese
Editore: Springer-Verlag New York Inc, 2014
ISBN 10: 331906598X ISBN 13: 9783319065984
Da: Revaluation Books, Exeter, Regno Unito
EUR 150,21
Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 2014 edition. 103 pages. 9.25x6.25x0.50 inches. In Stock.
Da: Buchpark, Trebbin, Germania
EUR 67,35
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | With the onset of massive cosmological data collection through media such as the Sloan Digital Sky Survey (SDSS), galaxy classification has been accomplished for the most part with the help of citizen science communities like Galaxy Zoo. Seeking the wisdom of the crowd for such Big Data processing has proved extremely beneficial. However, an analysis of one of the Galaxy Zoo morphological classification data sets has shown that a significant majority of all classified galaxies are labelled as ¿Uncertain¿.This book reports on how to use data mining, more specifically clustering, to identify galaxies that the public has shown some degree of uncertainty for as to whether they belong to one morphology type or another. The book shows the importance of transitions between different data mining techniques in an insightful workflow. It demonstrates that Clustering enables to identify discriminating features in the analysed data sets, adopting a novel feature selection algorithms called Incremental Feature Selection (IFS). The book shows the use of state-of-the-art classification techniques, Random Forests and Support Vector Machines to validate the acquired results. It is concluded that a vast majority of these galaxies are, in fact, of spiral morphology with a small subset potentially consisting of stars, elliptical galaxies or galaxies of other morphological variants.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 193,86
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 184,35
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 217,38
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 86,24
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Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 86,24
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Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer International Publishing, 2014
ISBN 10: 331906598X ISBN 13: 9783319065984
Da: moluna, Greven, Germania
EUR 92,27
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents recent applications of Big Data research to AstronomyDemonstrates the application of Big data to the Galaxy Zoo project, where a large collection of galaxy images are annotated by citizen scientistsPresents a Data Clustering Approa.
Lingua: Inglese
Editore: Springer International Publishing, 2016
ISBN 10: 3319383280 ISBN 13: 9783319383286
Da: moluna, Greven, Germania
EUR 93,00
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents recent applications of Big Data research to AstronomyDemonstrates the application of Big data to the Galaxy Zoo project, where a large collection of galaxy images are annotated by citizen scientistsPresents a Data Clustering Approa.
Da: Majestic Books, Hounslow, Regno Unito
EUR 141,19
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand pp. 105.
Da: Majestic Books, Hounslow, Regno Unito
EUR 145,34
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand pp. xii + 105 54 Illus. (24 Col.).
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 142,95
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 105.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 147,03
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. xii + 105.
Lingua: Inglese
Editore: Springer, Springer Apr 2014, 2014
ISBN 10: 331906598X ISBN 13: 9783319065984
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 106,99
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -With the onset of massive cosmological data collection through media such as the Sloan Digital Sky Survey (SDSS), galaxy classification has been accomplished for the most part with the help of citizen science communities like Galaxy Zoo. Seeking the wisdom of the crowd for such Big Data processing has proved extremely beneficial. However, an analysis of one of the Galaxy Zoo morphological classification data sets has shown that a significant majority of all classified galaxies are labelled as ¿Uncertain¿.This book reports on how to use data mining, more specifically clustering, to identify galaxies that the public has shown some degree of uncertainty for as to whether they belong to one morphology type or another. The book shows the importance of transitions between different data mining techniques in an insightful workflow. It demonstrates that Clustering enables to identify discriminating features in the analysed data sets, adopting a novel feature selection algorithms called Incremental Feature Selection (IFS). The book shows the use of state-of-the-art classification techniques, Random Forests and Support Vector Machines to validate the acquired results. It is concluded that a vast majority of these galaxies are, in fact, of spiral morphology with a small subset potentially consisting of stars, elliptical galaxies or galaxies of other morphological variants.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 120 pp. Englisch.