Logo

Algorithms for Clustering Data

Large book cover: Algorithms for Clustering Data

Algorithms for Clustering Data
by

Publisher: Prentice Hall
ISBN/ASIN: 013022278X
ISBN-13: 9780130222787
Number of pages: 334

Description:
This book will be useful for those in the scientific community who gather data and seek tools for analyzing and interpreting data. It will be a valuable reference for scientists in a variety of disciplines and can serve as a textbook for a graduate course in exploratory data analysis.

Home page url

Download or read it online for free here:
Download link
(39MB, PDF)

Similar books

Book cover: Knapsack Problems: Algorithms and Computer ImplementationsKnapsack Problems: Algorithms and Computer Implementations
by - John Wiley & Sons
The book on exact and approximate algorithms for a number of important problems in the field of integer linear programming, which the authors refer to as 'knapsack'. Includes knapsack problems such as binary, bounded, unbounded or binary multiple.
(17849 views)
Book cover: Algorithms and Data Structures: With Applications to Graphics and GeometryAlgorithms and Data Structures: With Applications to Graphics and Geometry
by - Prentice Hall
Contents: Programming environments for motion, graphics, and geometry; Programming concepts - beyond notation; Objects, algorithms, programs; Complexity of problems and algorithms; Data structures; Interaction between algorithms and data structures.
(9131 views)
Book cover: Algorithms and Data Structures: The Basic ToolboxAlgorithms and Data Structures: The Basic Toolbox
by - Springer
This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, etc.
(14634 views)
Book cover: AlgorithmsAlgorithms
by - Addison-Wesley Professional
This textbook surveys the most important algorithms and data structures in use today. Applications to science, engineering, and industry are a key feature of the text. We motivate each algorithm by examining its impact on specific applications.
(12863 views)