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mljar-api-R

A simple R wrapper for mljar.com API. It allows MLJAR users to create Machine Learning models with few lines of code:

library(mljar)

model <- mljar_fit(x.training, y.training, validx=x.validation, validy=y.validation,
                proj_title="Project title", exp_title="experiment title",
                algorithms = c("logreg"), metric = "logloss")

predicted_values <- mljar_predict(model, x.to.predict, "Project title")

That’s all folks! Yeah, I know, this makes Machine Learning super easy! You can use this code for following Machine Learning tasks: * Binary classification (your target has only two unique values) * Regression (your target value is continuous) * More is coming soon!

How to install

You can install mljar directly from CRAN:

install.packages("mljar")

Alternatively, you can install the latest development version from GitHub using devtools:

devtools::install_github("mljar/mljar-api-R")

How to use it

  1. Create an account at mljar.com and login.
  2. Please go to your users settings (top, right corner).
  3. Get your token, for example ‘exampleexampleexample’.
  4. Set environment variable MLJAR_TOKEN with your token value in shell:

    export MLJAR_TOKEN=exampleexampleexample

    or directly in RStudio:

    Sys.setenv(MLJAR_TOKEN="examplexampleexample")
  5. That’s all, you are ready to use MLJAR in your R code!

What’s going on?

Examples

Soon

Testing

To run tests use simple command in your R session:

devtools::test()