CRAN/E | superml

superml

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

Installation

About

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.

github.com/saraswatmks/superml
Bug report	File report

Key Metrics

Version	0.5.7
R	≥ 3.6
Published	2024-02-18 68 days ago
Needs compilation?	yes
License	GPL-3
License	File
CRAN checks	superml results

Downloads

Yesterday	42 +147%
Last 7 days	152 +9%
Last 30 days	647 -15%
Last 90 days	1.995 +2%
Last 365 days	8.466 -55%

Maintainer

Manish Saraswat

manish06saraswat@gmail.com

Authors

Manish Saraswat

aut / cre

Material

README
NEWS
Reference manual
Package source

Vignettes

Guide to CountVectorizer
How to use TfidfVectorizer in R ?
Introduction to SuperML

macOS

r-release	arm64
r-oldrel	arm64
r-release	x86_64

Windows

r-devel	x86_64
r-release	x86_64
r-oldrel	x86_64

Old Sources

superml archive

Depends

R	≥ 3.6
R6	≥ 2.2

Imports

data.table	≥ 1.10
Rcpp	≥ 1.0
assertthat	≥ 0.2
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
e1071	≥ 1.7

LinkingTo

Rcpp
BH
RcppArmadillo