Rodríguez Galiano VF., Sánchez Castillo M., Chica Olmo M., Chica Rivas M. Machine learning predictive models for mineral prospectivity: an evaluation of Neural Networks, Random Forest, Regression Trees and Support Vector machines. Ore Geology Reviews. 2015;71:804-818.
Abstract Machine learning algorithms (MLAs) such us artificial neural networks (ANNs), regression trees (RTs), random forest (RF) and support vector machines (SVMs) are powerful data driven methods that are relatively less widely used in the mapping of mineral prospectivity, and thus have not been comparatively evaluated together thoroughly in this field. The performances of a […]Consultar publicación