Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365987163X ISBN 13: 9783659871634
Lingua: Inglese
Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloPaperback. Condizione: Brand New. 52 pages. 8.66x5.91x0.12 inches. In Stock.
Editore: LAP Lambert Academic Publishing Mai 2016, 2016
ISBN 10: 365987163X ISBN 13: 9783659871634
Lingua: Inglese
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -Feature selection is the first task of any learning approach to define a relevant set of features. Several methods are proposed to deal with the problem of feature selection including filter, wrapper and embedded methods. In this work, we focus on feature subset selection to select a minimally sized subset of optimal features. Feature Selection is optimization problem; genetic algorithm based attribute subset selection using naïve bayes classifier is used for this purpose. GABASS are found to be the best technique for selection purpose when there is very large population. The GABASS provides good results and their power lies in the good adaptation to the various and fast changing environments.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch.
Editore: LAP Lambert Academic Publishing, 2016
ISBN 10: 365987163X ISBN 13: 9783659871634
Lingua: Inglese
Da: preigu, Osnabrück, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Attribute Selection with Genetic Algorithm | Genetic Algorithm Based Attributes Subset Selection Using Naive Bays Classifier | Bhupendra Kumar (u. a.) | Taschenbuch | 52 S. | Englisch | 2016 | LAP Lambert Academic Publishing | EAN 9783659871634 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365987163X ISBN 13: 9783659871634
Lingua: Inglese
Da: Mispah books, Redhill, SURRE, Regno Unito
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Aggiungi al carrellopaperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Editore: LAP Lambert Academic Publishing Mai 2016, 2016
ISBN 10: 365987163X ISBN 13: 9783659871634
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 35,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Feature selection is the first task of any learning approach to define a relevant set of features. Several methods are proposed to deal with the problem of feature selection including filter, wrapper and embedded methods. In this work, we focus on feature subset selection to select a minimally sized subset of optimal features. Feature Selection is optimization problem; genetic algorithm based attribute subset selection using naïve bayes classifier is used for this purpose. GABASS are found to be the best technique for selection purpose when there is very large population. The GABASS provides good results and their power lies in the good adaptation to the various and fast changing environments. 52 pp. Englisch.
Editore: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365987163X ISBN 13: 9783659871634
Lingua: Inglese
Da: moluna, Greven, Germania
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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: Kumar BhupendraDR Somesh Kumar presently spearheads the IT department in NIET, Gr. Noida, India. He has completed his MCA in 2000, ME (CS&E) in 2006, PhD (CS) in 2011. Since 2000, he has been in teaching profession. Prof Bhupendra Ku.
Editore: LAP Lambert Academic Publishing, 2016
ISBN 10: 365987163X ISBN 13: 9783659871634
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 35,90
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Feature selection is the first task of any learning approach to define a relevant set of features. Several methods are proposed to deal with the problem of feature selection including filter, wrapper and embedded methods. In this work, we focus on feature subset selection to select a minimally sized subset of optimal features. Feature Selection is optimization problem; genetic algorithm based attribute subset selection using naïve bayes classifier is used for this purpose. GABASS are found to be the best technique for selection purpose when there is very large population. The GABASS provides good results and their power lies in the good adaptation to the various and fast changing environments.