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mlr3viz: Visualization Extension for machine learning package mlr3
We are planning to make a R package mlr3viz to implement the visualization for machine learning analysis in mlr3 package. mlr package was first released to CRAN in 2013. Its core design and architecture date back even further. The addition of many features has led to a feature creep which makes mlr hard to maintain and hard to extend. We also think that while mlr was nicely extensible in some parts (learners, measures, etc.), other parts were less easy to extend from the outside. Also, many helpful R libraries did not exist at the time mlr was created, and their inclusion would result in non-trivial API changes.
mlr3 package is currently work-in-progress and focused on the basic building blocks for machine learning only. Some advanced features of the monolithic mlr are now shipped in multiple extension packages. One of the most important features, visualization, is planned to be included in mlr3viz package (This project).
mlr package included a lot of visualization features. They will be integrated into this mlr3viz package. As far as I know, there is no other packages specially developed for data visualization of machine learning results.
- We are going to make an usable mlr3viz package, providing functions for visualization of mlr3 results, with documents and vignette;
- The visualization functions will be proposed based on the design and needs of mlr3 package;
- The visualization functions in mlr package will be integrated into the new package;
Machine learning is very popular both in academic area and in the R community. As one of the most important and comprehensive machine learning package in R, mlr3 needs a visualization package to support its extensive usage in different area. The goal of mlr3viz package is providing user friendly visualization features for machine learning analysis results from mlr3. So that the users can focus on more important aspects of their projects and don’t need to worry about data and result visualization from machine learning analysis.
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Bernd Bischl bernd.bischl@stat.uni-muenchen.de is a Professor at the Ludwig-Maximilians-University Munich. He is an expert in machine learning, the author and maintainer of mlr package.
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Lars Kotthoff larsko@uwyo.edu is an Assistant Professor in University of Wyoming. He is an expert in machine learning, the author of mlr package.
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Michel Lang lang@statistik.tu-dortmund.de is the author and maintainer of mlr3 package. He doesn't have enough time to be a mentor. But will provide support and help in the mentoring.