SAT-Based Encodings for Optimal Decision Trees with Explicit Paths-Reference-Cited by-同舟云学术

SAT-Based Encodings for Optimal Decision Trees with Explicit Paths

Published:2020 Issue: Volume: Page:501-518
ISSN:0302-9743
Container-title:Theory and Applications of Satisfiability Testing – SAT 2020
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Author:

Janota Mikoláš^ORCID,Morgado António^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-51825-7_35

Reference38 articles.

1. Bertsimas, D., Dunn, J.: Optimal classification trees. Mach. Learn. 106(7), 1039–1082 (2017). https://doi.org/10.1007/s10994-017-5633-9

2. Lecture Notes in Computer Science;C Bessiere,2009

3. Biere, A.: CaDiCaL, Lingeling, PLingeling, Treengeling and YalSAT entering the SAT competition 2017. In: Balyo,T., Heule, M., Järvisalo, M. (eds.) SAT Competition 2017: Solver and Benchmark Descriptions, pp. 14–15. University of Helsinki (2017)

4. Biere, A., Heule, M., van Maaren, H., Walsh, T. (eds.): Handbook of Satisfiability, Frontiers in Artificial Intelligence and Applications, vol. 185, p. 980. IOS Press, Amsterdam (2009)

5. Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001). https://doi.org/10.1023/A:1010933404324

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