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.
| Version: |
0.1.4 |
| Depends: |
R (≥ 3.1.0) |
| Imports: |
backports, checkmate (≥ 1.9.3), data.table, digest, lgr (≥
0.3.0), Metrics, mlbench, mlr3misc (≥ 0.1.5), paradox, uuid, R6 |
| Suggests: |
bibtex, callr, datasets, evaluate, future (≥ 1.9.0), future.apply (≥ 1.1.0), future.callr, Matrix, rpart, testthat, titanic |
| Published: |
2019-10-28 |
| Author: |
Michel Lang  [cre,
aut],
Bernd Bischl
[aut],
Jakob Richter
[aut],
Patrick Schratz
[aut],
Giuseppe Casalicchio
[ctb],
Stefan Coors
[ctb],
Quay Au [ctb],
Martin Binder [aut] |
| Maintainer: |
Michel Lang <michellang at gmail.com> |
| BugReports: |
https://github.com/mlr-org/mlr3/issues |
| License: |
LGPL-3 |
| URL: |
https://mlr3.mlr-org.com, https://github.com/mlr-org/mlr3 |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| In views: |
MachineLearning |
| CRAN checks: |
mlr3 results |