Predictive Clustering

Authors: Blockeel, H., Dzeroski, S., Struyf, J., Zenko, B.

  • Features a new data mining approach: predictive clustering trees and rules
  • Presents a higher efficiency of the learning and prediction process
  • Provides straightforward content in an easy-to-understand manner
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  • ISBN 978-1-4614-1147-5
  • Digitally watermarked, DRM-free
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Hardcover ca. $99.00
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  • Due: April 24, 2025
  • ISBN 978-1-4614-1146-8
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About this book

This book introduces a novel paradigm for machine learning and data mining called predictive clustering, which covers a broad variety of learning tasks and offers a fresh perspective on existing techniques. The book presents an informal introduction to predictive clustering, describing learning tasks and settings, and then continues with a formal description of the paradigm, explaining algorithms for learning predictive clustering trees and predictive clustering rules, as well as presenting the applicability of these learning techniques to a broad range of tasks. Variants of decision tree learning algorithms are also introduced. Finally, the book offers several significant applications in ecology and bio-informatics. The book is written in a straightforward and easy-to-understand manner, aimed at varied readership, ranging from researchers with an interest in machine learning techniques to practitioners of data mining technology in the areas of ecology and bioinformatics.

Buy this book

eBook  
  • ISBN 978-1-4614-1147-5
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover ca. $99.00
price for USA
  • Due: April 24, 2025
  • ISBN 978-1-4614-1146-8
  • Free shipping for individuals worldwide

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Bibliographic Information

Bibliographic Information
Book Title
Predictive Clustering
Authors
Copyright
2025
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media, LLC
eBook ISBN
978-1-4614-1147-5
Hardcover ISBN
978-1-4614-1146-8
Edition Number
1
Number of Pages
V, 240
Topics