Flexible and Robust Machine Learning Using mlr3 in R

Getting Started


Bernd Bischl, Raphael Sonabend, Lars Kotthoff, Michel Lang


  • Marc Becker
  • Przemysław Biecek
  • Martin Binder
  • Bernd Bischl
  • Lukas Burk
  • Giuseppe Casalicchio
  • Susanne Dandl
  • Sebastian Fischer
  • Natalie Foss
  • Lars Kotthoff
  • Michel Lang
  • Florian Pfisterer
  • Damir Pulatov
  • Lennart Schneider
  • Patrick Schratz
  • Raphael Sonabend
  • Marvin N. Wright

Welcome to the Machine Learning in R universe. This is the online version of the upcoming book Flexible and Robust Machine Learning Using mlr3 in R. This book will teach you about the mlr3 universe of packages, from machine learning methodology to implementations of complex algorithmic pipelines. We will cover how to use the mlr3 family of packages for data processing, fitting and training of machine learning models, tuning and hyperparameter optimization, feature selection, pipelines, data preprocessing, and model interpretability. In addition we will look at how our interface works beyond classification and regression settings to other fields including survival analysis, clustering, and more. Finally, for readers interested in technical details, we will look at implementation and decision decisions, as well as error handling and parallelization.

We hope you enjoy reading our book and always welcome comments and feedback. If you notice any mistakes in the book we would appreciate if you could open an issue in the mlr3book issue tracker. All content in this book is licensed under CC BY-NC-SA 4.0.