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Attribute selection genetic algorithm di kumar bhupendra (5 risultati)

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  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2016

    365987163X / 9783659871634

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    Condizione: Nuovo

    EUR 67,39

    EUR 11,94 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 1 disponibile

    Paperback. Condizione: Brand New. 52 pages. 8.66x5.91x0.12 inches. In Stock.

  • Lingua: Inglese

    Editore: LAP Lambert Academic Publishing Mai 2016, 2016

    365987163X / 9783659871634

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    EUR 35,90

    EUR 23,00 spedizione 
    Spedito da Germania a U.S.A.

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    Taschenbuch. 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.…

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2016

    365987163X / 9783659871634

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    • Print on Demand

    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Condizione: Nuovo

    EUR 35,90

    EUR 35,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 1 disponibile

    Taschenbuch. 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.…

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing, 2016

    365987163X / 9783659871634

    • Brossura
    • Print on Demand

    Da: moluna, Greven, Germaniamoluna

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    Condizione: Nuovo

    EUR 31,27

    EUR 48,99 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: Più di 20 disponibili

    Condizione: 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. …

  • Lingua: Inglese

    Editore: LAP LAMBERT Academic Publishing Mai 2016, 2016

    365987163X / 9783659871634

    • Brossura
    • Print on Demand

    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Condizione: Nuovo

    EUR 35,90

    EUR 60,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 1 disponibile

    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.…