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superml
View on CRAN: Click
here
Download and install superml package within the R console
Install from CRAN:
install.packages("superml")
Install from Github:
library("remotes")
install_github("cran/superml")
Install by package version:
library("remotes")
install_version("superml", "0.5.7")
Attach the package and use:
library("superml")
Maintained by
Manish Saraswat
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.superml . https://github.com/saraswatmks/superml/issues . https://github.com/saraswatmks/superml . superml results . superml.pdf . superml_0.5.7.tar.gz . superml_0.5.7.zip . superml_0.5.7.zip . superml_0.5.7.zip . superml_0.5.7.tgz . superml_0.5.7.tgz . superml_0.5.7.tgz . superml_0.5.7.tgz . superml_0.5.7.tgz . superml_0.5.7.tgz . superml archive . https://CRAN.R-project.org/package=superml .
First Published: 2018-12-30
Latest Update: 2024-02-18
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.
How to cite:
Manish Saraswat (2018). superml: Build Machine Learning Models Like Using Python's Scikit-Learn Library in R. R package version 0.5.7, https://cran.r-project.org/web/packages/superml. Accessed 29 Mar. 2025.
Previous versions and publish date:
Other packages that cited superml R package
View superml citation profile
Other R packages that superml depends,
imports, suggests or enhances
Complete documentation for superml
Functions, R codes and Examples using
the superml R package
Some associated functions: CountVectorizer . Counter . GridSearchCV . KMeansTrainer . KNNTrainer . LMTrainer . LabelEncoder . NBTrainer . RFTrainer . RandomSearchCV . TfIdfVectorizer . XGBTrainer . bm25 . bm_25 . check_package . cla_train . createFolds . dot . dotmat . kFoldMean . normalise1d . normalise2d . reg_train . smoothMean . sort_index . testdata .
Some associated R codes: CountVectorizer.R . GridSearch.R . KMeansTrainer.R . KNNTrainer.R . LMTrainer.R . LabelEncoder.R . NBTrainer.R . RandomForest.R . RandomSearch.R . RcppExports.R . TfidfVectorizer.R . XGBoost.R . bm25.R . createFolds.R . data.R . super_utils.R . target_encoders.R . Full superml package functions and examples
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