msgl
Multinomial Sparse Group Lasso
Multinomial logistic regression with sparse group lasso penalty. Simultaneous feature selection and parameter estimation for classification. Suitable for high dimensional multiclass classification with many classes. The algorithm computes the sparse group lasso penalized maximum likelihood estimate. Use of parallel computing for cross validation and subsampling is supported through the 'foreach' and 'doParallel' packages. Development version is on GitHub, please report package issues on GitHub.
- http://www.sciencedirect.com/science/article/pii/S0167947313002168
- GitHub
- File a bug report
- msgl results
- msgl.pdf
- Version2.3.9
- R version≥ 3.2.4
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release05/08/2019
Documentation
Team
Niels Richard Hansen
Martin Vincent
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- Depends3 packages
- Imports4 packages
- Suggests2 packages
- Linking To5 packages