Large-Scale Parallel Data Mining
Editat de Mohammed J. Zaki, Ching-Tien Hoen Limba Engleză Paperback – 23 feb 2000
Preț: 319.75 lei
Preț vechi: 399.68 lei
-20% Nou
Puncte Express: 480
Preț estimativ în valută:
56.58€ • 66.44$ • 49.66£
56.58€ • 66.44$ • 49.66£
Carte tipărită la comandă
Livrare economică 28 ianuarie-11 februarie 26
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9783540671947
ISBN-10: 3540671943
Pagini: 272
Ilustrații: VIII, 260 p.
Dimensiuni: 155 x 235 x 15 mm
Greutate: 0.42 kg
Ediția:2000
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540671943
Pagini: 272
Ilustrații: VIII, 260 p.
Dimensiuni: 155 x 235 x 15 mm
Greutate: 0.42 kg
Ediția:2000
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
Large-Scale Parallel Data Mining.- Parallel and Distributed Data Mining: An Introduction.- Mining Frameworks.- The Integrated Delivery of Large-Scale Data Mining: The ACSys Data Mining Project.- A High Performance Implementation of the Data Space Transfer Protocol (DSTP).- Active Mining in a Distributed Setting.- Associations and Sequences.- Efficient Parallel Algorithms for Mining Associations.- Parallel Branch-and-Bound Graph Search for Correlated Association Rules.- Parallel Generalized Association Rule Mining on Large Scale PC Cluster.- Parallel Sequence Mining on Shared-Memory Machines.- Classification.- Parallel Predictor Generation.- Efficient Parallel Classification Using Dimensional Aggregates.- Learning Rules from Distributed Data.- Clustering.- Collective, Hierarchical Clustering from Distributed, Heterogeneous Data.- A Data-Clustering Algorithm on Distributed Memory Multiprocessors.
Caracteristici
Includes supplementary material: sn.pub/extras