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A machine learning approach to tungsten prospectivity modelling using knowledge-driven feature extraction and model confidence (2020)
Journal Article
Yeomans, C. M., Shail, R. K., Grebby, S., Nykänen, V., Middleton, M., & Lusty, P. A. (2020). A machine learning approach to tungsten prospectivity modelling using knowledge-driven feature extraction and model confidence. Geoscience Frontiers, 11(6), 2067-2081. https://doi.org/10.1016/j.gsf.2020.05.016

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... Read More about A machine learning approach to tungsten prospectivity modelling using knowledge-driven feature extraction and model confidence.