superml

Build Machine Learning Models Like Using Python's Scikit-Learn Library in R

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.

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Description file content

Package
superml
Type
Package
Title
Build Machine Learning Models Like Using Python's Scikit-Learn Library in R
Version
0.5.0
Maintainer
Manish Saraswat
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
BugReports
https://github.com/saraswatmks/superml/issues
Depends
R(>= 3.5), R6(>= 2.2)
Imports
data.table (>= 1.10), assertthat (>= 0.2), parallel, doParallel (>= 1.0), Metrics (>= 0.1)
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), kableExtra, tm(>= 0.7), Matrix(>= 1.2), e1071(>= 1.7)
RoxygenNote
7.0.1
VignetteBuilder
knitr
NeedsCompilation
no
Packaged
2019-11-28 21:33:10 UTC; m.saraswat
Author
Manish Saraswat [aut, cre]
Repository
CRAN
Date/Publication
2019-11-29 09:10:03 UTC

install.packages('superml')

0.5.0

16 days ago

https://github.com/saraswatmks/superml

Manish Saraswat

GPL-3 | file LICENSE

Depends on

R(>= 3.5), R6(>= 2.2)

Imports

data.table (>= 1.10), assertthat (>= 0.2), parallel, doParallel (>= 1.0), Metrics (>= 0.1)

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), kableExtra, tm(>= 0.7), Matrix(>= 1.2), e1071(>= 1.7)

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