Automatic Design of Decision-Tree Induction Algorithms

  • Rodrigo C. Barros
  • André C.P.L.F de Carvalho
  • Alex A. Freitas

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Rodrigo C. Barros, André C. P. L. F. de Carvalho, Alex A. Freitas
    Pages 1-5
  3. Rodrigo C. Barros, André C. P. L. F. de Carvalho, Alex A. Freitas
    Pages 7-45
  4. Rodrigo C. Barros, André C. P. L. F. de Carvalho, Alex A. Freitas
    Pages 47-58
  5. Rodrigo C. Barros, André C. P. L. F. de Carvalho, Alex A. Freitas
    Pages 59-76
  6. Rodrigo C. Barros, André C. P. L. F. de Carvalho, Alex A. Freitas
    Pages 77-139
  7. Rodrigo C. Barros, André C. P. L. F. de Carvalho, Alex A. Freitas
    Pages 141-170
  8. Rodrigo C. Barros, André C. P. L. F. de Carvalho, Alex A. Freitas
    Pages 171-176

About this book

Introduction

Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction algorithm regardless of the data, the authors argue on the benefits that a bias-fitting strategy could bring to decision-tree induction, in which the ultimate goal is the automatic generation of a decision-tree induction algorithm tailored to the application domain of interest. For such, they discuss how one can effectively discover the most suitable set of components of decision-tree induction algorithms to deal with a wide variety of applications through the paradigm of evolutionary computation, following the emergence of a novel field called hyper-heuristics.

"Automatic Design of Decision-Tree Induction Algorithms" would be highly useful for machine learning and evolutionary computation students and researchers alike.

Keywords

Automatic Design Decision trees Evolutionary Computation Hyper-heuristics Machine Learning

Authors and affiliations

  • Rodrigo C. Barros
    • 1
  • André C.P.L.F de Carvalho
    • 2
  • Alex A. Freitas
    • 3
  1. 1.Pontifícia Universidade Católica do Rio Grande do Sul, Faculdade de InformáticaPorto AlegreBrazil
  2. 2.Universidade de São Paulo, Instituto de Ciências Matemáticas e de ComputaçãoSão CarlosBrazil
  3. 3.University of Kent, School of ComputingCanterburyUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-14231-9
  • Copyright Information The Author(s) 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-14230-2
  • Online ISBN 978-3-319-14231-9
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • About this book