mglasso
Multiscale Graphical Lasso
Inference of Multiscale graphical models with neighborhood selection approach. The method is based on solving a convex optimization problem combining a Lasso and fused-group Lasso penalties. This allows to infer simultaneously a conditional independence graph and a clustering partition. The optimization is based on the Continuation with Nesterov smoothing in a Shrinkage-Thresholding Algorithm solver (Hadj-Selem et al. 2018) <doi:10.1109/TMI.2018.2829802> implemented in python.
- Version0.1.2
- R versionunknown
- LicenseMIT
- Needs compilation?No
- Last release09/08/2022
Documentation
Team
Edmond Sanou
Christophe Ambroise
Show author detailsRolesThesis advisorTung Le
Show author detailsRolesContributorGeneviève Robin
Show author detailsRolesThesis advisor
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- Imports8 packages
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