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Minerals, Volume 12, Issue 8
August 2022 - 144 articles
Cover Story: Mapping of prospective areas using machine learning methods is a multi-criteria task that involves using positive and negative examples during the training process. However, negative locations are uncertain and need to be generated according to data-driven approaches or geological knowledge. With this in mind, this study compares two criteria for constraining the creation negative data sets and analyzes the effects associated with this process by generating hundreds of potential maps. Three widely used algorithms, including random forest, support vector machine, and k-nearest neighbors, were applied to conduct prospectivity mapping of the eastern sector of the Juruena Mineral Province, Brazil. View this paper
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Minerals - ISSN 2075-163X