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The goal of SuperML is to provide sckit-learn's fit,predict,transform standard way of building machine learning models in R. It is build on top of latest r-packages which provides optimized way of training machine learning models.


You can install latest stable cran version using (recommended):

install.packages("superml", dependencies=TRUE) # to install all dependencies at once

You can install superml from github with:

# install.packages("devtools")


In superml, every machine learning algorithm is called as a trainer. Following is the list of trainers available as of today:

In addition, there are other useful functions to support modeling tasks such as:

To compute text similarity, following functions are available:


Any machine learning model can be trained using the following steps:


# random forest
rf <- RFTrainer$new(n_estimators = 100)
rf$fit(iris, "Species")
pred <- rf$predict(iris)


The documentation can be found here: SuperML Documentation

Contributions & Support

SuperML is my ambitious effort to help people train machine learning models in R as easily as they do in python. I encourage you to use this library, post bugs and feature suggestions in the issues above.

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superml documentation built on April 28, 2020, 9:05 a.m.