mlr3pipelines: Preprocessing Operators and Pipelines for 'mlr3'

Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.

See also

Useful links:

• https://mlr3pipelines.mlr-org.com

• https://github.com/mlr-org/mlr3pipelines

• Report bugs at https://github.com/mlr-org/mlr3pipelines/issues

Author

Maintainer: Martin Binder mlr.developer@mb706.com

Authors:

• Florian Pfisterer pfistererf@googlemail.com (ORCID)

• Lennart Schneider lennart.sch@web.de (ORCID)

• Bernd Bischl bernd_bischl@gmx.net (ORCID)

• Michel Lang michellang@gmail.com (ORCID)

• Sebastian Fischer sebf.fischer@gmail.com (ORCID)

• Susanne Dandl dandl.susanne@googlemail.com

Other contributors:

• Keno Mersmann keno.mersmann@gmail.com [contributor]

• Maximilian Mücke muecke.maximilian@gmail.com (ORCID) [contributor]

• Lona Koers lona.koers@gmail.com [contributor]