2023
DOI: 10.3390/min13080997
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Discrimination of Quartz Genesis Based on Explainable Machine Learning

Abstract: Quartz is an important mineral in many metal deposits and can provide important indications about the deposit's origin through its chemical composition. However, traditional low-dimensional analysis methods are ineffective in utilizing quartz's chemical composition to reveal the deposit's origin type. In this study, 1140 quartz samples from eight geological environments were collected, and three machine learning (ML) models—random forest, eXtremely Greedy tree Boosting (XGBoost), and light gradient boosting ma… Show more

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Cited by 5 publications
(2 citation statements)
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“…The SVM is one of the most commonly employed algorithms in ore exploration prediction, and proves highly effective in mineral exploration mapping, lithology classification, alteration phase identification, and geochemical discrimination [98,102,105,106].…”
Section: Support Vector Machinementioning
confidence: 99%
“…The SVM is one of the most commonly employed algorithms in ore exploration prediction, and proves highly effective in mineral exploration mapping, lithology classification, alteration phase identification, and geochemical discrimination [98,102,105,106].…”
Section: Support Vector Machinementioning
confidence: 99%
“…The discrimination of quartz genesis based on explainable machine learning was presented in ref. [24]. Machine learning methods centered around the non-destructive testing of dynamic properties of vacuum-insulated glazing-type composite panels was discussed in ref.…”
mentioning
confidence: 99%