mlr3 (0.1.4)

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Machine Learning in R - Next Generation.

https://mlr3.mlr-org.com
https://github.com/mlr-org/mlr3
http://cran.r-project.org/web/packages/mlr3

Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.

Maintainer: Michel Lang
Author(s): Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>), Giuseppe Casalicchio [ctb] (<https://orcid.org/0000-0001-5324-5966>), Stefan Coors [ctb] (<https://orcid.org/0000-0002-7465-2146>), Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>), Martin Binder [aut]

License: LGPL-3

Uses: backports, checkmate, data.table, digest, lgr, Metrics, mlbench, mlr3misc, paradox, R6, uuid, Matrix, rpart, testthat, bibtex, evaluate, future, titanic, callr, future.apply, future.callr

Released 15 days ago.


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