Dataset for: Machine learning application to automatically classify heavy minerals in river sand by using SEM/EDS data

Among them, three tables include the EDS data of analyzed elements including 90-second elemental data of 2255 grains, 40-second elemental data of 492 grains and 6- second elemental data of 320 grains, respectively. The tables 4-7 include the confusion matrixes based on datasets of different analyzin...

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1. Verfasser:	Hu, Xiumian
Format:	Dataset
Sprache:	eng
Schlagworte:	Artificial Intelligence FOS: Earth and related environmental sciences Geochemistry Geology Heavy Mineral Machine Learning Mineralogy Sedimentology
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creator	Hu, Xiumian
description	Among them, three tables include the EDS data of analyzed elements including 90-second elemental data of 2255 grains, 40-second elemental data of 492 grains and 6- second elemental data of 320 grains, respectively. The tables 4-7 include the confusion matrixes based on datasets of different analyzing times and different decision attributes.
doi_str_mv	10.17632/t6t82b2h7h.1
format	Dataset
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identifier	DOI: 10.17632/t6t82b2h7h.1
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language	eng
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subjects	Artificial Intelligence FOS: Earth and related environmental sciences Geochemistry Geology Heavy Mineral Machine Learning Mineralogy Sedimentology
title	Dataset for: Machine learning application to automatically classify heavy minerals in river sand by using SEM/EDS data
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