A machine learning approach to tungsten prospectivity modelling using knowledge-driven feature extraction and model confidence
Novel mineral prospectivity modelling presented here applies knowledge-driven feature extraction to a data-driven machine learning approach for tungsten mineralisation. The method emphasises the importance of appropriate model evaluation and develops a new Confidence Metric to generate spatially ref...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2020-11-01
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Series: | Geoscience Frontiers |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1674987120301353 |