A practical approach for discriminating tectonic settings of basaltic rocks using machine learning-Reference-Cited by-同舟云学术

A practical approach for discriminating tectonic settings of basaltic rocks using machine learning

Published:2023-09 Issue: Volume:19 Page:100132
ISSN:2590-1974
Container-title:Applied Computing and Geosciences
language:en
Short-container-title:Applied Computing and Geosciences

Author:

Nakamura Kentaro^ORCID

Publisher

Elsevier BV

Subject

General Computer Science,Geology

Reference36 articles.

1. An analysis of transformations revisited, rebutted;Box;J. Am. Stat. Assoc.,1982

2. Random forests;Breiman;Mach. Learn.,2001

3. Le diagramme La/10-Y/15-Nb/8: un outil pour la discrimination des series volcaniques et lamise en evidence des processus demelange et/ou de contamination crustale;Cabanis;Compte Rendus de I’Académie des Sciences Series II,1989

4. Xgboost: a scalable tree boosting system;Chen,2016

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