DESCRIPTION

Package: diffPrivML
Title: Differential Private Machine Learning
Version: 0.0.0.900
Authors@R: c(
    person("Terence", "Tam", email = "terencet@stanford.edu", role = c("aut", "cre")),
    person("Yifan", "Gong", email = "yifan.gong717@gmail.com", role = c("aut")))
Description: A machine learning library that aims to put differential private 
    enhanced ML algorithms in the hands of data practitioners. End users do not 
    need to worry about *HOW* to perturb the data to release their models; the ML 
    algorithm itself makes the guarantee.
Depends: R (>= 3.4.3)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: R6, caret, glmnet
Suggests: knitr,
    rmarkdown,
    testthat
VignetteBuilder: knitr
Collate: 
    'noiseFunctions.R'
    'DPLogisticRegressionClassifier.R'
    'DPNaiveBayesClassifier.R'
    'DPRandomDecisionTreeClassifier.R'
    'datasets.R'
    'diffPrivML.R'