Partitional Clustering Algorithms

Editors: Celebi, M. Emre (Ed.)

  • Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in real-world applications
  • Discusses algorithms specifically designed for partitional clustering
  • Covers center-based, competitive learning, density-based, fuzzy, graph-based, grid-based, metaheuristic, and model-based approaches
see more benefits

Buy this book

eBook $109.00
price for USA (gross)
  • ISBN 978-3-319-09259-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.99
price for USA
  • ISBN 978-3-319-09258-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $149.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: August 31, 2016
  • ISBN 978-3-319-34798-1
  • Free shipping for individuals worldwide
About this book

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.

About the authors

Dr. Emre Celebi is an Associate Professor with the Department of Computer Science, at Louisiana State University in Shreveport.

Reviews

“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 of readers, including scientists, students, and researchers.” (L. State, Computing Reviews, April, 2015)


Table of contents (12 chapters)

  • Recent Developments in Model-Based Clustering with Applications

    Melnykov, Volodymyr (et al.)

    Pages 1-39

  • Accelerating Lloyd’s Algorithm for k-Means Clustering

    Hamerly, Greg (et al.)

    Pages 41-78

  • Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

    Celebi, M. Emre (et al.)

    Pages 79-98

  • Nonsmooth Optimization Based Algorithms in Cluster Analysis

    Bagirov, Adil M. (et al.)

    Pages 99-146

  • Fuzzy Clustering Algorithms and Validity Indices for Distributed Data

    Vendramin, L. (et al.)

    Pages 147-192

Buy this book

eBook $109.00
price for USA (gross)
  • ISBN 978-3-319-09259-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.99
price for USA
  • ISBN 978-3-319-09258-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $149.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: August 31, 2016
  • ISBN 978-3-319-34798-1
  • Free shipping for individuals worldwide
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Partitional Clustering Algorithms
Editors
  • M. Emre Celebi
Copyright
2015
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-09259-1
DOI
10.1007/978-3-319-09259-1
Hardcover ISBN
978-3-319-09258-4
Softcover ISBN
978-3-319-34798-1
Edition Number
1
Number of Pages
X, 415
Number of Illustrations and Tables
33 b/w illustrations, 45 illustrations in colour
Topics