Package: superml
Type: Package
Title: Build Machine Learning Models Like Using Python's Scikit-Learn
        Library in R
Version: 0.5.3
Authors@R: person("Manish", "Saraswat", email = "manish06saraswat@gmail.com",
          role = c("aut", "cre"))
Maintainer: Manish Saraswat <manish06saraswat@gmail.com>
Description: The idea is to provide a standard interface 
             to users who use both R and Python for building machine learning models. 
             This package provides a scikit-learn's fit, predict interface to 
             train machine learning models in R.    
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/saraswatmks/superml
BugReports: https://github.com/saraswatmks/superml/issues
Depends: R(>= 3.5), R6(>= 2.2)
Imports: data.table (>= 1.10), Rcpp (>= 1.0), assertthat (>= 0.2),
        Metrics (>= 0.1)
LinkingTo: Rcpp, BH, RcppArmadillo
Suggests: knitr, rlang, testthat, rmarkdown, naivebayes(>= 0.9),
        ClusterR(>= 1.1), FNN(>= 1.1), ranger(>= 0.10), caret(>= 6.0),
        xgboost(>= 0.6), glmnet(>= 2.0), e1071(>= 1.7)
RoxygenNote: 7.0.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-04-27 18:56:51 UTC; m.saraswat
Author: Manish Saraswat [aut, cre]
Repository: CRAN
Date/Publication: 2020-04-28 07:40:02 UTC
Built: R 4.0.5; x86_64-w64-mingw32; 2022-04-17 22:25:56 UTC; windows
Archs: i386, x64
