Grouping Multidimensional Data - 9783540283485
Un libro in lingua di Kogan Jacob (EDT) Nicholas Charles K. (EDT) Teboulle Marc (EDT) edito da Springer Verlag, 2006
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Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection.
Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as application and evaluation of algorithms, and thus provide an excellent state-of-the-art overview.
The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas.
Informazioni bibliografiche
- Titolo del Libro in lingua: Grouping Multidimensional Data
- Sottotitolo: Recent Advances in Clustering
- Lingua: English
- Autori : Kogan Jacob (EDT) Nicholas Charles K. (EDT) Teboulle Marc (EDT)
- Editore: Springer Verlag
- Collana: Springer Verlag (Hardcover)
- Data di Pubblicazione: 15 Gennaio '06
- Genere: COMPUTERS
- Argomenti : Cluster analysis Data mining Classification automatique (Statistique
- Pagine: 268
- Dimensioni mm: 234 x 158 x 19
- ISBN-10: 354028348X
- EAN-13: 9783540283485