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.
Version: 0.5.7 Depends: R (≥ 3.6), 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) Published: 2024-02-18 DOI: 10.32614/CRAN.package.superml Author: Manish Saraswat [aut, cre] Maintainer: Manish Saraswat <manish06saraswat at gmail.com> BugReports: https://github.com/saraswatmks/superml/issues License: GPL-3 | file LICENSE URL: https://github.com/saraswatmks/superml NeedsCompilation: yes Materials: README NEWS CRAN checks: superml results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=superml to link to this page.
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