Partitional Clustering Algorithms
M. Emre Celebi (Ed.)
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Description for Partitional Clustering Algorithms
Hardback. Editor(s): Celebi, M. Emre. Num Pages: 415 pages, 33 black & white illustrations, 45 colour illustrations, 74 black & white tables, biograp. BIC Classification: TJK; TTBM; UT. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 24. Weight in Grams: 855.
This book focuses on partitional clustering algorithms, which are commonly used in engineering and computer scientific applications. The goal of this volume is to summarize the state-of-the-art in partitional clustering. The book includes such topics as center-based clustering, competitive learning clustering and density-based clustering. Each chapter is contributed by a leading expert in the field.
This book focuses on partitional clustering algorithms, which are commonly used in engineering and computer scientific applications. The goal of this volume is to summarize the state-of-the-art in partitional clustering. The book includes such topics as center-based clustering, competitive learning clustering and density-based clustering. Each chapter is contributed by a leading expert in the field.
Product Details
Publisher
Springer International Publishing AG
Format
Hardback
Publication date
2014
Condition
New
Weight
737g
Number of Pages
415
Place of Publication
Cham, Switzerland
ISBN
9783319092584
SKU
V9783319092584
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About M. Emre Celebi (Ed.)
Dr. Emre Celebi is an Associate Professor with the Department of Computer Science, at Louisiana State University in Shreveport.
Reviews for Partitional Clustering Algorithms
“The content of the book is really outstanding in terms of the clarity of the discourse and the variety of well-selected examples. … The book brings substantial contributions to the field of partitional clustering from both the theoretical and practical points of view, with the concepts and algorithms presented in a clear and accessible way. It addresses a wide range ... Read more