Skip to main content

Distributionally Robust Formulation and Model Selection for the Graphical Lasso

Project description

Robust Selection

PyPI version Binder

Python Package by C Tran, P Cisneros-Velarde, A Petersen and S-Y Oh

This repository provides a Python package for Robust Selection algorithm for estimation of the graphical lasso regularization parameter.

P Cisneros-Velarde, A Petersen and S-Y Oh (2020). Distributionally Robust Formulation and Model Selection for the Graphical Lasso. Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics. [PMLR][Papers with Code]

CV vs. RobSel

Dependencies

The code contained in this repository was tested on the following configuration of Python:

  • python=3.7.4
  • robust-selection=0.0.7
  • numpy=1.17.4
  • scipy=1.3.1
  • scikit-learn=0.22.1
  • networkx=2.4
  • pandas=0.25.3

Installation

pip install robust-selection

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

robust-selection-0.0.8.tar.gz (2.8 kB view hashes)

Uploaded Source

Built Distribution

robust_selection-0.0.8-py3-none-any.whl (3.9 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page