Predictive Clustering

Overview

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 ...

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Overview

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.

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Product Details

  • ISBN-13: 9781461411468
  • Publisher: Springer New York
  • Publication date: 3/14/2017
  • Edition description: 2017
  • Edition number: 1
  • Pages: 240

Table of Contents

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
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