Happy Holidays—Our $30 Gift Card just for you, and books ship free! Shop now>>

Unsupervised Learning Algorithms

Editors: Celebi, M. Emre, Aydin, Kemal (Eds.)

Free Preview
  • Contains the state-of-the-art in unsupervised learning in a single comprehensive volume
  • Features numerous step-by-step tutorials help the reader to learn quickly
  • Includes several tips on how to protect flash sites from hackers and a special chapter on next generation Flash that prepares readers for the future
see more benefits

Buy this book

eBook 85,59 €
price for Spain (gross)
  • ISBN 978-3-319-24211-8
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 103,99 €
price for Spain (gross)
  • ISBN 978-3-319-24209-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 103,99 €
price for Spain (gross)
  • ISBN 978-3-319-79590-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity among researchers and practitioners. The authors outline how these algorithms have found numerous applications including pattern recognition, market basket analysis, web mining, social network analysis, information retrieval, recommender systems, market research, intrusion detection, and fraud detection. They present how the difficulty of developing theoretically sound approaches that are amenable to objective evaluation have resulted in the proposal of numerous unsupervised learning algorithms over the past half-century. The intended audience includes researchers and practitioners who are increasingly using unsupervised learning algorithms to analyze their data. Topics of interest include anomaly detection, clustering, feature extraction, and applications of unsupervised learning. Each chapter is contributed by a leading expert in the field.

Reviews

“The book provides a valuable survey of an area of both research and application, particularly as massive datasets have become available. … The book can be recommended to anyone interested in getting an overview of this fast-moving research and application area. Because each chapter has a comprehensive bibliography, the book can serve as an entry point for those wishing to work in or with unsupervised learning.” (J. P. E. Hodgson, Computing Reviews, computingreviews.com, August, 2016)


Table of contents (18 chapters)

Table of contents (18 chapters)

Buy this book

eBook 85,59 €
price for Spain (gross)
  • ISBN 978-3-319-24211-8
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 103,99 €
price for Spain (gross)
  • ISBN 978-3-319-24209-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 103,99 €
price for Spain (gross)
  • ISBN 978-3-319-79590-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Unsupervised Learning Algorithms
Editors
  • M. Emre Celebi
  • Kemal Aydin
Copyright
2016
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-24211-8
DOI
10.1007/978-3-319-24211-8
Hardcover ISBN
978-3-319-24209-5
Softcover ISBN
978-3-319-79590-4
Edition Number
1
Number of Pages
X, 558
Number of Illustrations
59 b/w illustrations, 101 illustrations in colour
Topics