Predictive Clustering
Springer (Publisher)
Will be published approx. on 14. July 2099
Online / Databases
V, 240 pages
978-1-4614-1147-5 (ISBN)
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Description
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.
More details
Series
Language
English
Place of publication
New York
United States
Publishing group
Springer US
Target group
Adult education
Illustrations
V, 240 p.
ISBN-13
978-1-4614-1147-5 (9781461411475)
Schweitzer Classification
Other editions
Additional editions
Hendrik Blockeel | Saso Dzeroski | Jan Struyf
Predictive Clustering
Book
04/2025
Springer
€96.00
Shipment within 15-20 days
Content
Introduction.- What is predictive clustering?.- Motivation: A variety of predictive learning tasks.- Some basic approaches to prediction and clustering.- Formalizing predictive clustering.- Predictive clustering trees.- Predictive clustering rules.- Distances and prototype functions.- Predictive Clustering with Constraints.- Relational PCTs.- Applications in environmental sciences.- Applications in bioinformatics.- Clus