Automatic Design of Decision-Tree Induction Algorithms (SpringerBriefs in Computer Science)

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

  • 出版商: Springer
  • 出版日期: 2015-03-03
  • 售價: $2,500
  • 貴賓價: 9.5$2,375
  • 語言: 英文
  • 頁數: 176
  • 裝訂: Paperback
  • ISBN: 3319142305
  • ISBN-13: 9783319142302
  • 相關分類: Algorithms-data-structuresComputer-Science
  • 海外代購書籍(需單獨結帳)

商品描述

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.