Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200443726 ISBN 13: 9786200443724
Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Statistical Analysis of Complex Data | Dimensionality reduction and classification methods | Mario Fordellone | Taschenbuch | 84 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200443724 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Okt 2019, 2019
ISBN 10: 6200443726 ISBN 13: 9786200443724
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 39,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Statistical learning (SL) is the study of the generalizable extraction of knowledge from data (Friedman et al. 2001). The concept of learning is used when human expertise does not exist, humans are unable to explain their expertise, solution changes in time, solution needs to be adapted to particular cases. The principal algorithms used in SL are classified in: supervised learning (e.g. regression and classification), unsupervised learning (e.g. association and clustering), semi-supervised, it combines both labeled and unlabeled examples to generate an appropriate function or classifier. Following this research idea, in this book we propose a good review on the more recent statistical models used to solve the dimensionality problem recently discussed. 84 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200443726 ISBN 13: 9786200443724
Da: moluna, Greven, Germania
EUR 34,25
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Fordellone MarioDr. Mario Fordellone is a teaching assistant at LUISS University of Rome and research fellow at La Sapienza. He has demonstrated skills in Statistics, Research, Mathematical Modeling, and Programming.Statistical l.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Okt 2019, 2019
ISBN 10: 6200443726 ISBN 13: 9786200443724
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 39,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Statistical learning (SL) is the study of the generalizable extraction of knowledge from data (Friedman et al. 2001). The concept of learning is used when human expertise does not exist, humans are unable to explain their expertise, solution changes in time, solution needs to be adapted to particular cases. The principal algorithms used in SL are classified in: supervised learning (e.g. regression and classification), unsupervised learning (e.g. association and clustering), semi-supervised, it combines both labeled and unlabeled examples to generate an appropriate function or classifier. Following this research idea, in this book we propose a good review on the more recent statistical models used to solve the dimensionality problem recently discussed.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200443726 ISBN 13: 9786200443724
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 40,89
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Statistical learning (SL) is the study of the generalizable extraction of knowledge from data (Friedman et al. 2001). The concept of learning is used when human expertise does not exist, humans are unable to explain their expertise, solution changes in time, solution needs to be adapted to particular cases. The principal algorithms used in SL are classified in: supervised learning (e.g. regression and classification), unsupervised learning (e.g. association and clustering), semi-supervised, it combines both labeled and unlabeled examples to generate an appropriate function or classifier. Following this research idea, in this book we propose a good review on the more recent statistical models used to solve the dimensionality problem recently discussed.