Automatic Design of Decision-Tree Induction Algorithms

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Synopsis

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.

Book details

Edition:
2015
Series:
SpringerBriefs in Computer Science
Author:
Rodrigo C. Barros, André C.P.L.F de Carvalho, Alex A. Freitas
ISBN:
9783319142319
Related ISBNs:
9783319142302
Publisher:
Springer International Publishing
Pages:
N/A
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2019-09-06
Usage restrictions:
Copyright
Copyright date:
2015
Copyright by:
N/A 
Adult content:
No
Language:
English
Categories:
Computers and Internet, Nonfiction