Machine learning results and code

Jamil, Ahsan

doi:10.6084/m9.figshare.24328870.v1

Title: Machine learning results and code

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Abstract

Results for all the Four MLP-NN, RF, XGBR, and RF algorithms for each of geophysical array`s and machine learning python code is provided.

Authors:

Jamil, Ahsan

New Mexico State Univ., Las Cruces, NM (United States); New Mexico State Univ., Las Cruces, NM (United States)

Publication Date:: Tue Oct 17 00:00:00 EDT 2023

DOE Contract Number:: SC0023132

Research Org.:: New Mexico State University, Las Cruces, NM (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Subject:: 58 GEOSCIENCES; Boosting; Electrical resistivity; Geophysics; Machine learning; Neural networks; Random forests

OSTI Identifier:: 2520488

DOI:: https://doi.org/10.6084/m9.figshare.24328870.v1

Citation Formats


                    Jamil, Ahsan. Machine learning results and code.  United States: N. p., 2023. 
        Web.  doi:10.6084/m9.figshare.24328870.v1.

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                    Jamil, Ahsan. Machine learning results and code.  United States.  doi:https://doi.org/10.6084/m9.figshare.24328870.v1

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                    Jamil, Ahsan. 2023.  
"Machine learning results and code".  United States.  doi:https://doi.org/10.6084/m9.figshare.24328870.v1.  https://www.osti.gov/servlets/purl/2520488. Pub date:Tue Oct 17 00:00:00 EDT 2023

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@article{osti_2520488,

  title        = {Machine learning results and code},

  author       = {Jamil, Ahsan},

  abstractNote = {Results for all the Four MLP-NN, RF, XGBR, and RF algorithms for each of geophysical array`s and machine learning python code is provided.},

  doi          = {10.6084/m9.figshare.24328870.v1},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Oct 17 00:00:00 EDT 2023},

  month        = {Tue Oct 17 00:00:00 EDT 2023}

}

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DOI: https://doi.org/10.6084/m9.figshare.24328870.v1

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