A Survey of Evolutionary Algorithms for Decision-Tree Induction
Data
2012-05-01
Autores
Basgalupp, Marcio Porto 
Tipo
Artigo
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Resumo
This paper presents a survey of evolutionary algorithms that are designed for decision-tree induction. in this context, most of the paper focuses on approaches that evolve decision trees as an alternate heuristics to the traditional top-down divide-and-conquer approach. Additionally, we present some alternative methods that make use of evolutionary algorithms to improve particular components of decision-tree classifiers. the paper's original contributions are the following. First, it provides an up-to-date overview that is fully focused on evolutionary algorithms and decision trees and does not concentrate on any specific evolutionary approach. Second, it provides a taxonomy, which addresses works that evolve decision trees and works that design decision-tree components by the use of evolutionary algorithms. Finally, a number of references are provided that describe applications of evolutionary algorithms for decision-tree induction in different domains. At the end of this paper, we address some important issues and open questions that can be the subject of future research.
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Citação
Ieee Transactions On Systems Man and Cybernetics Part C-applications and Reviews. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 42, n. 3, p. 291-312, 2012.