Learning optimal decision trees using constraint programming

Decision trees are among the most popular classification models in machine learning. Traditionally, they are learned using greedy algorithms. However, such algorithms pose several disadvantages: it is difficult to limit the size of the decision trees while maintaining a good classification accuracy,...

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Bibliographic Details

Published in:	Constraints : an international journal Vol. 25; no. 3-4; pp. 226 - 250
Main Authors:	Verhaeghe, Hélène, Nijssen, Siegfried, Pesant, Gilles, Quimper, Claude-Guy, Schaus, Pierre
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.12.2020
Subjects:	Artificial Intelligence Computer Science Operations Research/Decision Theory Optimization Original Research CoverSize Decision Tree AND/OR search tree Caching
ISSN:	1383-7133, 1572-9354
Online Access:	Get full text
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