GAP Safe Screening Rules for Sparse-Group-Lasso
In this repository, we propose an efficient implementation to solve the Sparse-Group-Lasso (with optional elastic net regularization) using a block coordinate descent algorithm with safe screening rules.
Examples on synthetic dataset are presented in examples.ipynb (example.py for a pure python version).
This package has the following requirements:
- Python (version 2.7)
- Numpy (tested with version 0.16)
- Scipy (at least version 0.16.1)
We recommend to install or update anaconda (at least version 0.16.1).
The compilation proceed as follows:
- $ cython sgl_fast.pyx
- $ python setup.py build_ext --inplace