Published January 19, 2023 | Version 1.2
Dataset Open

Identifying serpentine minerals by their chemical compositions with machine learning (dataset and python code)

  • 1. Guangzhou Institute of Geochemistry, Chinese Academy of Sciences
  • 2. CSIRO, Mineral Resources
  • 3. Ohio University
  • 4. Indian Institute of Technology, Kharagpur
  • 5. University of Minnesota
  • 6. University of California, Los Angeles
  • 7. University of Toronto
  • 8. State University of New York at Fredonia
  • 9. Zhejiang University

Description

The dataset and python code for the manuscript of Identifying serpentine minerals by their chemical compositions with machine learning (submitted to American Geologist)

Files

Distribution_plot.ipynb

Files (10.8 MB)

Name Size Download all
md5:ca74e85d8218f242f3eab540f5344b39
2.5 MB Preview Download
md5:bc67b9ca633ffc895d2e1f0454667bed
5.6 MB Preview Download
md5:668adbaa774d85a7c4138552bd42e71d
405.0 kB Download
md5:e98531de2486facbbf150835fe77a3f4
400.3 kB Download
md5:7340f1d78430e8dca0d7c510d7f527ab
1.2 MB Preview Download
md5:01dc7e30b4e099551098ffabc685c6ff
772.4 kB Preview Download