Machine Learning Methods for Quantifying Uncertainty in Prospectivity Mapping of Magmatic-Hydrothermal Gold Deposits: A Case Study from Juruena Mineral Province, Northern Mato Grosso, Brazil
Mineral prospectivity mapping (MPM), like other geoscience fields, is subject to a variety of uncertainties. When data about unfavorable sites to find deposits (i.e., drill intersections to barren rocks) is lacking in MPM using machine learning (ML) methods, the synthetic generation of negative data...
Main Authors: | Victor Silva dos Santos, Erwan Gloaguen, Vinicius Hector Abud Louro, Martin Blouin |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-07-01
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Series: | Minerals |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-163X/12/8/941 |
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