The goal of SuperML is to provide sckit-learn's
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") install.packages("superml", dependencies=TRUE) # to install all dependencies at once
You can install superml from github with:
# install.packages("devtools") devtools::install_github("saraswatmks/superml")
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:
data(iris) library(superml) # random forest rf <- RFTrainer$new(n_estimators = 100) rf$fit(iris, "Species") pred <- rf$predict(iris)
The documentation can be found here: SuperML Documentation
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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