Abstract
Learning Planar Ising Models is a software package written in Matlab for learning relationships among variable in a dataset using graphical models. The software package implements a generally-applicable algorithm for learning planar Ising models from any multivariate dataset. The code provides an algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. The software includes demonstrations of the algorithm in simulations and for applications on publicly available datasets. Details of the algorithm, demonstration simulations, and applications are given in Johnson, et al; 2016. Reference: Johnson, J. K., Oyen, D., Chertkov, M., and Netrapalli, P. (2016). Learning planar Ising models. Journal of Machine Learning Research.
- Developers:
- Release Date:
- 2022-08-31
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Licenses:
-
BSD 3-clause "New" or "Revised" License
- Sponsoring Org.:
-
USDOE Laboratory Directed Research and Development (LDRD) ProgramPrimary Award/Contract Number:AC52-06NA25396
- Code ID:
- 92670
- Site Accession Number:
- C22025
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Country of Origin:
- United States
Citation Formats
Oyen, Diane.
Learning Planar Ising Models Software.
Computer Software.
https://github.com/lanl/planar-ising.
USDOE Laboratory Directed Research and Development (LDRD) Program.
31 Aug. 2022.
Web.
doi:10.11578/dc.20220915.9.
Oyen, Diane.
(2022, August 31).
Learning Planar Ising Models Software.
[Computer software].
https://github.com/lanl/planar-ising.
https://doi.org/10.11578/dc.20220915.9.
Oyen, Diane.
"Learning Planar Ising Models Software." Computer software.
August 31, 2022.
https://github.com/lanl/planar-ising.
https://doi.org/10.11578/dc.20220915.9.
@misc{
doecode_92670,
title = {Learning Planar Ising Models Software},
author = {Oyen, Diane},
abstractNote = {Learning Planar Ising Models is a software package written in Matlab for learning relationships among variable in a dataset using graphical models. The software package implements a generally-applicable algorithm for learning planar Ising models from any multivariate dataset. The code provides an algorithm for learning the best planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. The software includes demonstrations of the algorithm in simulations and for applications on publicly available datasets. Details of the algorithm, demonstration simulations, and applications are given in Johnson, et al; 2016. Reference: Johnson, J. K., Oyen, D., Chertkov, M., and Netrapalli, P. (2016). Learning planar Ising models. Journal of Machine Learning Research.},
doi = {10.11578/dc.20220915.9},
url = {https://doi.org/10.11578/dc.20220915.9},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20220915.9}},
year = {2022},
month = {aug}
}