Predictive Clustering
Springer (Publisher)
Published on 25. April 2025
Book
Hardback
V, 240 pages
978-1-4614-1146-8 (ISBN)
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
Edition
2025 ed.
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Professional/practitioner
Product notice
sewn/stitched
Cloth over boards
Illustrations
V, 240 p.
Dimensions
Height: 235 mm
Width: 193 mm
ISBN-13
978-1-4614-1146-8 (9781461411468)
Schweitzer Classification
Other editions
Additional editions
Hendrik Blockeel | Saso Dzeroski | Jan Struyf
Predictive Clustering
Online / Databases
approx. 07/2099
Springer
Unfortunately, price unknown
Article exhausted; check different version
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