WLogit: Variable Selection in High-Dimensional Logistic Regression Models using a Whitening Approach (original) (raw)

It proposes a novel variable selection approach in classification problem that takes into account the correlations that may exist between the predictors of the design matrix in a high-dimensional logistic model. Our approach consists in rewriting the initial high-dimensional logistic model to remove the correlation between the predictors and in applying the generalized Lasso criterion.

Documentation:

Downloads:

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=WLogitto link to this page.