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PrivateLR  

Differentially Private Regularized Logistic Regression
View on CRAN: Click here


Download and install PrivateLR package within the R console
Install from CRAN:
install.packages("PrivateLR")

Install from Github:
library("remotes")
install_github("cran/PrivateLR")

Install by package version:
library("remotes")
install_version("PrivateLR", "1.2-22")



Attach the package and use:
library("PrivateLR")
Maintained by
Staal A. Vinterbo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-03-23
Latest Update: 2018-03-20
Description:
Implements two differentially private algorithms for estimating L2-regularized logistic regression coefficients. A randomized algorithm F is epsilon-differentially private (C. Dwork, Differential Privacy, ICALP 2006 ), if |log(P(F(D) in S)) - log(P(F(D') in S))| <= epsilon for any pair D, D' of datasets that differ in exactly one record, any measurable set S, and the randomness is taken over the choices F makes.
How to cite:
Staal A. Vinterbo (2012). PrivateLR: Differentially Private Regularized Logistic Regression. R package version 1.2-22, https://cran.r-project.org/web/packages/PrivateLR. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0-21 (2012-03-23 06:48), 1.1-69 (2013-06-04 18:14), 1.2-21 (2014-10-31 16:16)
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Complete documentation for PrivateLR
Functions, R codes and Examples using the PrivateLR R package
Some associated functions: dplr . 
Some associated R codes: Full PrivateLR package functions and examples
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