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Feature Pathway Graphs using Random Forest Regressors

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/RFR-CLDERA
https://doi.org/10.11578/dc.20250806.4

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Abstract

SAND2025-04671O Feature Pathway Graphs using Random Forest Regressors is a software tool that uses machine learning to determine pathways of influence between features in data sets. It can be used as a surrogate method for casual discovery. The output creates pathway graphs between features of interest. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Developers:
Peterson, Matthew [1][2][3] ;  Brown, Meredith [1][2][3]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
Release Date:
2024-09-10
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Python
Version:
0.1
Licenses:
Other (Commercial or Open-Source): https://ip.sandia.gov
Sponsoring Org.:
Code ID:
160135
Site Accession Number:
SCR #3098.0
Research Org.:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Country of Origin:
United States

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/RFR-CLDERA
https://doi.org/10.11578/dc.20250806.4

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Citation Formats

Peterson, Matthew, and Brown, Meredith. Feature Pathway Graphs using Random Forest Regressors. Computer Software. https://github.com/sandialabs/RFR-CLDERA. USDOE. 10 Sep. 2024. Web. doi:10.11578/dc.20250806.4.
Peterson, Matthew, & Brown, Meredith. (2024, September 10). Feature Pathway Graphs using Random Forest Regressors. [Computer software]. https://github.com/sandialabs/RFR-CLDERA. https://doi.org/10.11578/dc.20250806.4.
Peterson, Matthew, and Brown, Meredith. "Feature Pathway Graphs using Random Forest Regressors." Computer software. September 10, 2024. https://github.com/sandialabs/RFR-CLDERA. https://doi.org/10.11578/dc.20250806.4.
@misc{ doecode_160135,
title = {Feature Pathway Graphs using Random Forest Regressors},
author = {Peterson, Matthew and Brown, Meredith},
abstractNote = {SAND2025-04671O Feature Pathway Graphs using Random Forest Regressors is a software tool that uses machine learning to determine pathways of influence between features in data sets. It can be used as a surrogate method for casual discovery. The output creates pathway graphs between features of interest. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.},
doi = {10.11578/dc.20250806.4},
url = {https://doi.org/10.11578/dc.20250806.4},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20250806.4}},
year = {2024},
month = {sep}
}