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. Ed(S): Kogan, Jacob; Nicholas, Charles; Teboulle, Marc - Grouping Multidimensional Data: Recent Advances in Clustering - 9783540283485 - V9783540283485
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Grouping Multidimensional Data: Recent Advances in Clustering

€ 128.65
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Description for Grouping Multidimensional Data: Recent Advances in Clustering hardcover. Addresses topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. This volume covers theoretical basics as well as application and evaluation of algorithms. Editor(s): Kogan, Jacob; Nicholas, Charles; Teboulle, Marc. Num Pages: 268 pages, 36 black & white tables, biography. BIC Classification: UN. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 20. Weight in Grams: 590.

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 ... Read more

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.

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Product Details

Format
Hardback
Publication date
2005
Publisher
Springer/Sci-Tech/Trade Germany
Number of pages
268
Condition
New
Number of Pages
268
Place of Publication
Berlin, Germany
ISBN
9783540283485
SKU
V9783540283485
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

About . Ed(S): Kogan, Jacob; Nicholas, Charles; Teboulle, Marc
Jacob Kogan is an Associate Professor in the Department of Mathematics and Statistics at the University of Maryland Baltimore County. Dr. Kogan received his Ph.D. in Mathematics from Weizmann Institute of Science, and has held teaching and research positions at the University of Toronto and Purdue University. His research interests include Text and Data Mining, Optimization, Calculus of Variations, Optimal ... Read more

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