tkdmah/iilasso: Independently Interpretable Lasso
Efficient algorithms for fitting linear / logistic regression model with Independently Interpretable Lasso. Takada, M., Suzuki, T., & Fujisawa, H. (2018). Independently Interpretable Lasso: A New Regularizer for Sparse Regression with Uncorrelated Variables. AISTATS. <http://proceedings.mlr.press/v84/takada18a/takada18a.pdf>.
Getting started
Browse package contents
Package details |
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| Author | Masaaki Takada |
| Maintainer | Masaaki Takada <tkdmah@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.0.3 |
| URL | http://proceedings.mlr.press/v84/takada18a/takada18a.pdf |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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