Browsing by Subject "Random forest"
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Development of a supervised classification method to construct 2D mineral maps on backscattered electron images Authors:
Publisher and Date:(Tubitak, 2020)The Mineral Liberation Analyzer (MLA) can be used to obtain mineral maps from backscattered electron (BSE) images of particles. This paper proposes an alternative methodology that includes random forest classification, a prospective machine learning algorithm, to develop mineral maps from BSE images. The results show that the overall accuracy and kappa statistic of the proposed method are 97% and 0.94, respectively, proving that random forest classification is accurate. The accuracy indicators ...