mlr3

mlr3-package

<img src="figures/logo.png?package=mlr3&version=0.3.0" align="right" alt="logo" width="120">
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.

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.

Michel Lang

Machine Learning in R - Next Generation

Bernd Bischl

Jakob Richter

Patrick Schratz

Giuseppe Casalicchio

Stefan Coors

Quay Au

Martin Binder

mlr3-package function

<ul>
<li>Book on mlr3: <a href="https://mlr3book.mlr-org.com">https://mlr3book.mlr-org.com</a></li>
<li>Use cases and examples: <a href="https://mlr3gallery.mlr-org.com">https://mlr3gallery.mlr-org.com</a></li>
<li>More classification and regression learners: mlr3learners</li>
<li>Preprocessing and machine learning pipelines: mlr3pipelines</li>
<li>Tuning of hyperparameters: mlr3tuning</li>
<li>Visualizations for many mlr3 objects: mlr3viz</li>
<li>Survival analysis and probabilistic regression: mlr3proba</li>
<li>Feature selection filters: mlr3filters</li>
<li>Interface to real (out-of-memory) data bases: mlr3db</li>
<li>Performance measures as plain functions: mlr3measures</li>
<li>Parallelization framework: future</li>
<li>Progress bars: progressr</li>
</ul>

Additional resources

<img src='figures/logo.png' align='right' alt='logo' width='120' />
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.

mlr3-package: mlr3: Machine Learning in R - Next Generation

Description

Arguments

Additional resources

References

See Also