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>.


This package provides efficient algorithms for fitting linear / logistic regression model with Independently Interpretable Lasso.

Installation

To install: install.packages("iilasso")

References

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

News

0.0.1 (2018-04-16)

  • First version. APIs can be changed later.

0.0.2 (2018-06-21)

  • Bug fix. (covariance matrix, random seed)

Reference manual

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install.packages("iilasso")

0.0.2 by Masaaki Takada, 6 months ago


http://proceedings.mlr.press/v84/takada18a/takada18a.pdf


Browse source code at https://github.com/cran/iilasso


Authors: Masaaki Takada


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Rcpp, Matrix

Suggests testthat, knitr, rmarkdown, MASS, parallel

Linking to Rcpp, BH


See at CRAN