2018
DOI: 10.1007/s00500-018-3646-3
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A multi-objective evolutionary approach to Pareto-optimal model trees

Abstract: This paper discusses the multi-objective evolutionary approach to induction of model trees. The model tree is a particular case of a decision tree designed to solve regression problems. Although the decision tree induction is inherently a multiobjective task, most of the conventional learning algorithms can only deal with a single objective that may possibly aggregate multiple objectives. The goal of this paper is to demonstrate how a set of non-dominated model trees can be obtained using the Global Model Tree… Show more

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Cited by 15 publications
(5 citation statements)
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“…Other works [15] (and [18], [20]- [22], even if they are not applied to RL tasks) induce trees using evolutionary approaches. However, these approaches only rely on an EA.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Other works [15] (and [18], [20]- [22], even if they are not applied to RL tasks) induce trees using evolutionary approaches. However, these approaches only rely on an EA.…”
Section: Methodsmentioning
confidence: 99%
“…In [20], the authors propose a multi-objective EA to evolve regression trees and model trees. They find a Pareto front for RMSE, the number of nodes, and the number of attributes.…”
Section: Related Workmentioning
confidence: 99%
“…Other works [11] (and [12,13,14,15], even if they are not applied to reinforcement learning tasks) induce trees by means of evolutionary approaches.…”
Section: Methodsmentioning
confidence: 99%
“…In [13], the authors propose a multi-objective EA to evolve regression trees and model trees. They use a Pareto front to optimize RMSE, number of nodes, number of attributes.…”
Section: Theorymentioning
confidence: 99%
“…The Review of Literature will discuss the related work of the study. Czajkowski and Kretowski, [25] discuss the multi-objective design approach to model-tree recognition. The model tree is a specific instance of a tree of preference built to take care of relapse problems.…”
Section: Literature Reviewmentioning
confidence: 99%