ISBN: 9786200300621 - optimized data clustering technique for categorical data: an efficient approach (6 résultats)

Affiner la recherche

  • Livres (6)

  • Neuf (6)

à

Fourchette de prix personnalisée (EUR)

à

  • Langue : anglais

    Edité par LAP LAMBERT Academic Publishing, 2019

    6200300623 / 9786200300621

    • Couverture souple

    Vendeur : preigu, Osnabrück, Allemagnepreigu

    Vendeur avec une évaluation de 5 étoiles
    Contacter le vendeur

    Etat: Neuf

    EUR 53,55

    EUR 70,00 expédition 
    Expédition depuis Allemagne vers Etats-Unis

    Quantité disponible : 5 disponibles

    Taschenbuch. Etat : Neu. Optimized Data Clustering Technique for Categorical Data | An Efficient Approach | Pallavi Chaudhari (u. a.) | Taschenbuch | 132 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200300621 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

  • Langue : anglais

    Edité par LAP LAMBERT Academic Publishing, 2019

    6200300623 / 9786200300621

    • Couverture souple

    Vendeur : Mispah books, Redhill, SURRE, Royaume-UniMispah books

    Vendeur avec une évaluation de 4 étoiles
    Contacter le vendeur

    Etat: Neuf

    EUR 185,37

    EUR 29,99 expédition 
    Expédition depuis Royaume-Uni vers Etats-Unis

    Quantité disponible : 1 disponible

    paperback. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

  • Langue : anglais

    Edité par LAP LAMBERT Academic Publishing Sep 2019, 2019

    6200300623 / 9786200300621

    • Couverture souple
    • impression à la demande

    Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.

    Vendeur avec une évaluation de 5 étoiles
    Contacter le vendeur

    Etat: Neuf

    EUR 61,90

    EUR 23,00 expédition 
    Expédition depuis Allemagne vers Etats-Unis

    Quantité disponible : 2 disponibles

    Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, a new clustering technique for categorical-data is introduced. Essentially, the effectiveness of a clustering technique is significantly determined by two aspects, the searching method and the proximity criteria. The proposed algorithm uses a genetic algorithm for clustering that is shown in the experiments to be an efficient clustering method for categorical-data. The proximity criteria adopt a rule-based information theoretical measure called weight of evidence. It finds the interesting patterns and measures the weight of these patterns that supporting the presence of an objective-value pair to be relevant to a cluster label. By summing up the total weight that the records acquire in the patterns due to presence of both the objective-value and the corresponding cluster label, the fitness in the chromosome is measured and hence how best the records are clustered together is seen. 132 pp. Englisch.…

  • Langue : anglais

    Edité par LAP LAMBERT Academic Publishing, 2019

    6200300623 / 9786200300621

    • Couverture souple
    • impression à la demande

    Vendeur : moluna, Greven, Allemagnemoluna

    Vendeur avec une évaluation de 5 étoiles
    Contacter le vendeur

    Etat: Neuf

    EUR 50,66

    EUR 48,99 expédition 
    Expédition depuis Allemagne vers Etats-Unis

    Quantité disponible : Plus de 20 disponibles

    Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chaudhari Dr. PallaviDr. Pallavi Chaudhari is Associate Professor and Head of Department of Information Technology (IT), Priyadarshini Institute of Engineering and Technology (PIET), Nagpur. She has 20 years of teaching expe.…

  • Langue : anglais

    Edité par LAP LAMBERT Academic Publishing, 2019

    6200300623 / 9786200300621

    • Couverture souple
    • impression à la demande

    Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH

    Vendeur avec une évaluation de 5 étoiles
    Contacter le vendeur

    Etat: Neuf

    EUR 69,44

    EUR 35,00 expédition 
    Expédition depuis Allemagne vers Etats-Unis

    Quantité disponible : 1 disponible

    Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, a new clustering technique for categorical-data is introduced. Essentially, the effectiveness of a clustering technique is significantly determined by two aspects, the searching method and the proximity criteria. The proposed algorithm uses a genetic algorithm for clustering that is shown in the experiments to be an efficient clustering method for categorical-data. The proximity criteria adopt a rule-based information theoretical measure called weight of evidence. It finds the interesting patterns and measures the weight of these patterns that supporting the presence of an objective-value pair to be relevant to a cluster label. By summing up the total weight that the records acquire in the patterns due to presence of both the objective-value and the corresponding cluster label, the fitness in the chromosome is measured and hence how best the records are clustered together is seen.…

  • Langue : anglais

    Edité par LAP LAMBERT Academic Publishing Sep 2019, 2019

    6200300623 / 9786200300621

    • Couverture souple
    • impression à la demande

    Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagnebuchversandmimpf2000

    Vendeur avec une évaluation de 5 étoiles
    Contacter le vendeur

    Etat: Neuf

    EUR 61,90

    EUR 60,00 expédition 
    Expédition depuis Allemagne vers Etats-Unis

    Quantité disponible : 1 disponible

    Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, a new clustering technique for categorical-data is introduced. Essentially, the effectiveness of a clustering technique is significantly determined by two aspects, the searching method and the proximity criteria. The proposed algorithm uses a genetic algorithm for clustering that is shown in the experiments to be an efficient clustering method for categorical-data. The proximity criteria adopt a rule-based information theoretical measure called weight of evidence. It finds the interesting patterns and measures the weight of these patterns that supporting the presence of an objective-value pair to be relevant to a cluster label. By summing up the total weight that the records acquire in the patterns due to presence of both the objective-value and the corresponding cluster label, the fitness in the chromosome is measured and hence how best the records are clustered together is seen.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 132 pp. Englisch.…