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WLogit: Variable Selection in High-Dimensional Logistic Regression Models using a Whitening Approach
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.
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Package details |
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| Author | Wencan Zhu |
| Maintainer | Wencan Zhu <wencan.zhu@yahoo.com> |
| License | GPL-2 |
| Version | 2.1 |
| Package repository | View on CRAN |
| Installation |
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