/L0Group

Grouped Variable Selection using L0 Regularization

Primary LanguagePython

Grouped Variable Selection with Discrete Optimization

Hussein Hazimeh, Rahul Mazumder, and Peter Radchenko

This is the accompanying code for our paper Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives.

This repo contains code for (i) approximate algorithms based on coordinate descent and combinatorial local search, and (ii) exact algorithms based on a custom branch-and-bound algorithm.

To get started please refer to Demo.ipynb

Prerequisites and Usage

The package is written in Python 3. It requires the following prerequisites:

  • numpy
  • scipy
  • numba
  • gurobi (only needed for the BnB algorithm)

See the Jupyter notebook Demo.ipynb for a demonstration on how to use the different algorithms.