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Evolutionary Algorithms for Global Decision Tree Induction

Evolutionary Algorithms for Global Decision Tree Induction

Marek Kretowski, Marcin Czajkowski
Copyright: © 2018 |Pages: 10
ISBN13: 9781522522553|ISBN10: 1522522557|EISBN13: 9781522522560
DOI: 10.4018/978-1-5225-2255-3.ch185
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MLA

Kretowski, Marek, and Marcin Czajkowski. "Evolutionary Algorithms for Global Decision Tree Induction." Encyclopedia of Information Science and Technology, Fourth Edition, edited by Mehdi Khosrow-Pour, D.B.A., IGI Global, 2018, pp. 2132-2141. https://doi.org/10.4018/978-1-5225-2255-3.ch185

APA

Kretowski, M. & Czajkowski, M. (2018). Evolutionary Algorithms for Global Decision Tree Induction. In M. Khosrow-Pour, D.B.A. (Ed.), Encyclopedia of Information Science and Technology, Fourth Edition (pp. 2132-2141). IGI Global. https://doi.org/10.4018/978-1-5225-2255-3.ch185

Chicago

Kretowski, Marek, and Marcin Czajkowski. "Evolutionary Algorithms for Global Decision Tree Induction." In Encyclopedia of Information Science and Technology, Fourth Edition, edited by Mehdi Khosrow-Pour, D.B.A., 2132-2141. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-2255-3.ch185

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Abstract

Decision trees represent one of the main predictive techniques in knowledge discovery. This chapter describes evolutionary induced trees, which are emerging alternatives to the greedy top-down solutions. Most typical tree-based system searches only for locally optimal decisions at each node and do not guarantee the optimal solution. Application of evolutionary algorithms to the problem of decision tree induction allows searching for the structure of the tree, tests in internal nodes and regression functions in the leaves (for model trees) at the same time. As a result, such globally induced decision tree is able to avoid local optima and usually leads to better prediction than the greedy counterparts.

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