These are the results of online meetings of the Meetup group "R User Group Rhein-Neckar" about the 'mlr3' package for "Machine Learning with R" that took place in July and August 2020.
- July 14, 19:00-19:40 -- Introducing 'mlr3'; first steps; example
- July 28, 19:00-19:40 -- Resampling, data preparation, benchmarking
- August 11, 19:00-19:40 -- Hyperparameter tuning, additional learners
Topics of discussion were how 'mlr3' does support different aspects of Machine Learning; how can 'mlr3' be used, pros and cons, applying it to example data, what else is needed, etc.
- 1. Introduction
- 2. Learning
- 3. Example
- 4. Preparing
- 5. Testing
- 6. Tuning
- Pipelining -- tbd.
- Visualization -- tbd.
For comparison we have added an application of the RandomForest package to the 'glass' data:
RandomForest Test