mlr-package

<img src="figures/logo.png?package=mlr&version=2.19.0" align="right" alt="logo" width="120">
Interface to a large number of classification and
 regression techniques, including machine-readable parameter
 descriptions. There is also an experimental extension for survival
 analysis, clustering and general, example-specific cost-sensitive
 learning. Generic resampling, including cross-validation,
 bootstrapping and subsampling. Hyperparameter tuning with modern
 optimization techniques, for single- and multi-objective problems.
 Filter and wrapper methods for feature selection. Extension of basic
 learners with additional operations common in machine learning, also
 allowing for easy nested resampling. Most operations can be
 parallelized.

Interface to a large number of classification and
regression techniques, including machine-readable parameter
descriptions. There is also an experimental extension for survival
analysis, clustering and general, example-specific cost-sensitive
learning. Generic resampling, including cross-validation,
bootstrapping and subsampling.  Hyperparameter tuning with modern
optimization techniques, for single- and multi-objective problems.
Filter and wrapper methods for feature selection. Extension of basic
learners with additional operations common in machine learning, also
allowing for easy nested resampling.  Most operations can be
parallelized.

Patrick Schratz

Machine Learning in R

Bernd Bischl

Michel Lang

Lars Kotthoff

Julia Schiffner

Jakob Richter

Zachary Jones

Giuseppe Casalicchio

Mason Gallo

Jakob Bossek

Erich Studerus

Leonard Judt

Tobias Kuehn

Pascal Kerschke

Florian Fendt

Philipp Probst

Xudong Sun

Janek Thomas

Bruno Vieira

Laura Beggel

Quay Au

Martin Binder

Florian Pfisterer

Stefan Coors

Steve Bronder

Alexander Engelhardt

Christoph Molnar

Annette Spooner

mlr-package function

Maintainer: Patrick Schratz <a href="/link/patrick.schratz%40gmail.com?package=mlr&version=2.19.0" data-mini-rdoc="mlr::patrick.schratz@gmail.com">patrick.schratz@gmail.com</a> (<a href="https://orcid.org/0000-0003-0748-6624">ORCID</a>)
Authors:<ul>
<li>Bernd Bischl <a href="/link/bernd_bischl%40gmx.net?package=mlr&version=2.19.0" data-mini-rdoc="mlr::bernd_bischl@gmx.net">bernd_bischl@gmx.net</a> (<a href="https://orcid.org/0000-0001-6002-6980">ORCID</a>)</li>
<li>Michel Lang <a href="/link/michellang%40gmail.com?package=mlr&version=2.19.0" data-mini-rdoc="mlr::michellang@gmail.com">michellang@gmail.com</a> (<a href="https://orcid.org/0000-0001-9754-0393">ORCID</a>)</li>
<li>Lars Kotthoff <a href="/link/larsko%40uwyo.edu?package=mlr&version=2.19.0" data-mini-rdoc="mlr::larsko@uwyo.edu">larsko@uwyo.edu</a></li>
<li>Julia Schiffner <a href="/link/schiffner%40math.uni-duesseldorf.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::schiffner@math.uni-duesseldorf.de">schiffner@math.uni-duesseldorf.de</a></li>
<li>Jakob Richter <a href="/link/code%40jakob-r.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::code@jakob-r.de">code@jakob-r.de</a></li>
<li>Zachary Jones <a href="/link/zmj%40zmjones.com?package=mlr&version=2.19.0" data-mini-rdoc="mlr::zmj@zmjones.com">zmj@zmjones.com</a></li>
<li>Giuseppe Casalicchio <a href="/link/giuseppe.casalicchio%40stat.uni-muenchen.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::giuseppe.casalicchio@stat.uni-muenchen.de">giuseppe.casalicchio@stat.uni-muenchen.de</a> (<a href="https://orcid.org/0000-0001-5324-5966">ORCID</a>)</li>
<li>Mason Gallo <a href="/link/masonagallo%40gmail.com?package=mlr&version=2.19.0" data-mini-rdoc="mlr::masonagallo@gmail.com">masonagallo@gmail.com</a></li>
</ul>Other contributors:<ul>
<li>Jakob Bossek <a href="/link/jakob.bossek%40tu-dortmund.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::jakob.bossek@tu-dortmund.de">jakob.bossek@tu-dortmund.de</a> (<a href="https://orcid.org/0000-0002-4121-4668">ORCID</a>) [contributor]</li>
<li>Erich Studerus <a href="/link/erich.studerus%40upkbs.ch?package=mlr&version=2.19.0" data-mini-rdoc="mlr::erich.studerus@upkbs.ch">erich.studerus@upkbs.ch</a> (<a href="https://orcid.org/0000-0003-4233-0182">ORCID</a>) [contributor]</li>
<li>Leonard Judt <a href="/link/leonard.judt%40tu-dortmund.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::leonard.judt@tu-dortmund.de">leonard.judt@tu-dortmund.de</a> [contributor]</li>
<li>Tobias Kuehn <a href="/link/tobi.kuehn%40gmx.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::tobi.kuehn@gmx.de">tobi.kuehn@gmx.de</a> [contributor]</li>
<li>Pascal Kerschke <a href="/link/kerschke%40uni-muenster.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::kerschke@uni-muenster.de">kerschke@uni-muenster.de</a> (<a href="https://orcid.org/0000-0003-2862-1418">ORCID</a>) [contributor]</li>
<li>Florian Fendt <a href="/link/flo_fendt%40gmx.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::flo_fendt@gmx.de">flo_fendt@gmx.de</a> [contributor]</li>
<li>Philipp Probst <a href="/link/philipp_probst%40gmx.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::philipp_probst@gmx.de">philipp_probst@gmx.de</a> (<a href="https://orcid.org/0000-0001-8402-6790">ORCID</a>) [contributor]</li>
<li>Xudong Sun <a href="/link/xudong.sun%40stat.uni-muenchen.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::xudong.sun@stat.uni-muenchen.de">xudong.sun@stat.uni-muenchen.de</a> (<a href="https://orcid.org/0000-0003-3269-2307">ORCID</a>) [contributor]</li>
<li>Janek Thomas <a href="/link/janek.thomas%40stat.uni-muenchen.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::janek.thomas@stat.uni-muenchen.de">janek.thomas@stat.uni-muenchen.de</a> (<a href="https://orcid.org/0000-0003-4511-6245">ORCID</a>) [contributor]</li>
<li>Bruno Vieira <a href="/link/bruno.hebling.vieira%40usp.br?package=mlr&version=2.19.0" data-mini-rdoc="mlr::bruno.hebling.vieira@usp.br">bruno.hebling.vieira@usp.br</a> [contributor]</li>
<li>Laura Beggel <a href="/link/laura.beggel%40web.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::laura.beggel@web.de">laura.beggel@web.de</a> (<a href="https://orcid.org/0000-0002-8872-8535">ORCID</a>) [contributor]</li>
<li>Quay Au <a href="/link/quay.au%40stat.uni-muenchen.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::quay.au@stat.uni-muenchen.de">quay.au@stat.uni-muenchen.de</a> (<a href="https://orcid.org/0000-0002-5252-8902">ORCID</a>) [contributor]</li>
<li>Martin Binder <a href="/link/ma.binder%40campus.lmu.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::ma.binder@campus.lmu.de">ma.binder@campus.lmu.de</a> [contributor]</li>
<li>Florian Pfisterer <a href="/link/pfistererf%40googlemail.com?package=mlr&version=2.19.0" data-mini-rdoc="mlr::pfistererf@googlemail.com">pfistererf@googlemail.com</a> [contributor]</li>
<li>Stefan Coors <a href="/link/stefan.coors%40gmx.net?package=mlr&version=2.19.0" data-mini-rdoc="mlr::stefan.coors@gmx.net">stefan.coors@gmx.net</a> [contributor]</li>
<li>Steve Bronder <a href="/link/sab2287%40columbia.edu?package=mlr&version=2.19.0" data-mini-rdoc="mlr::sab2287@columbia.edu">sab2287@columbia.edu</a> [contributor]</li>
<li>Alexander Engelhardt <a href="/link/alexander.w.engelhardt%40gmail.com?package=mlr&version=2.19.0" data-mini-rdoc="mlr::alexander.w.engelhardt@gmail.com">alexander.w.engelhardt@gmail.com</a> [contributor]</li>
<li>Christoph Molnar <a href="/link/christoph.molnar%40stat.uni-muenchen.de?package=mlr&version=2.19.0" data-mini-rdoc="mlr::christoph.molnar@stat.uni-muenchen.de">christoph.molnar@stat.uni-muenchen.de</a> [contributor]</li>
<li>Annette Spooner <a href="/link/a.spooner%40unsw.edu.au?package=mlr&version=2.19.0" data-mini-rdoc="mlr::a.spooner@unsw.edu.au">a.spooner@unsw.edu.au</a> [contributor]</li>
</ul>

Author

<img src='figures/logo.png' align='right' alt='logo' width='120' />
Interface to a large number of classification and
 regression techniques, including machine-readable parameter
 descriptions. There is also an experimental extension for survival
 analysis, clustering and general, example-specific cost-sensitive
 learning. Generic resampling, including cross-validation,
 bootstrapping and subsampling. Hyperparameter tuning with modern
 optimization techniques, for single- and multi-objective problems.
 Filter and wrapper methods for feature selection. Extension of basic
 learners with additional operations common in machine learning, also
 allowing for easy nested resampling. Most operations can be
 parallelized.

mlr: Machine Learning in R — mlr-package

Maintainer: Patrick Schratz <a href='mailto:patrick.schratz@gmail.com'>patrick.schratz@gmail.com</a> (<a href='https://orcid.org/0000-0003-0748-6624'>ORCID</a>)
Authors:<ul>
<li>Bernd Bischl <a href='mailto:bernd_bischl@gmx.net'>bernd_bischl@gmx.net</a> (<a href='https://orcid.org/0000-0001-6002-6980'>ORCID</a>)</li>
<li>Michel Lang <a href='mailto:michellang@gmail.com'>michellang@gmail.com</a> (<a href='https://orcid.org/0000-0001-9754-0393'>ORCID</a>)</li>
<li>Lars Kotthoff <a href='mailto:larsko@uwyo.edu'>larsko@uwyo.edu</a></li>
<li>Julia Schiffner <a href='mailto:schiffner@math.uni-duesseldorf.de'>schiffner@math.uni-duesseldorf.de</a></li>
<li>Jakob Richter <a href='mailto:code@jakob-r.de'>code@jakob-r.de</a></li>
<li>Zachary Jones <a href='mailto:zmj@zmjones.com'>zmj@zmjones.com</a></li>
<li>Giuseppe Casalicchio <a href='mailto:giuseppe.casalicchio@stat.uni-muenchen.de'>giuseppe.casalicchio@stat.uni-muenchen.de</a> (<a href='https://orcid.org/0000-0001-5324-5966'>ORCID</a>)</li>
<li>Mason Gallo <a href='mailto:masonagallo@gmail.com'>masonagallo@gmail.com</a></li>
</ul>

Other contributors:<ul>
<li>Jakob Bossek <a href='mailto:jakob.bossek@tu-dortmund.de'>jakob.bossek@tu-dortmund.de</a> (<a href='https://orcid.org/0000-0002-4121-4668'>ORCID</a>) [contributor]</li>
<li>Erich Studerus <a href='mailto:erich.studerus@upkbs.ch'>erich.studerus@upkbs.ch</a> (<a href='https://orcid.org/0000-0003-4233-0182'>ORCID</a>) [contributor]</li>
<li>Leonard Judt <a href='mailto:leonard.judt@tu-dortmund.de'>leonard.judt@tu-dortmund.de</a> [contributor]</li>
<li>Tobias Kuehn <a href='mailto:tobi.kuehn@gmx.de'>tobi.kuehn@gmx.de</a> [contributor]</li>
<li>Pascal Kerschke <a href='mailto:kerschke@uni-muenster.de'>kerschke@uni-muenster.de</a> (<a href='https://orcid.org/0000-0003-2862-1418'>ORCID</a>) [contributor]</li>
<li>Florian Fendt <a href='mailto:flo_fendt@gmx.de'>flo_fendt@gmx.de</a> [contributor]</li>
<li>Philipp Probst <a href='mailto:philipp_probst@gmx.de'>philipp_probst@gmx.de</a> (<a href='https://orcid.org/0000-0001-8402-6790'>ORCID</a>) [contributor]</li>
<li>Xudong Sun <a href='mailto:xudong.sun@stat.uni-muenchen.de'>xudong.sun@stat.uni-muenchen.de</a> (<a href='https://orcid.org/0000-0003-3269-2307'>ORCID</a>) [contributor]</li>
<li>Janek Thomas <a href='mailto:janek.thomas@stat.uni-muenchen.de'>janek.thomas@stat.uni-muenchen.de</a> (<a href='https://orcid.org/0000-0003-4511-6245'>ORCID</a>) [contributor]</li>
<li>Bruno Vieira <a href='mailto:bruno.hebling.vieira@usp.br'>bruno.hebling.vieira@usp.br</a> [contributor]</li>
<li>Laura Beggel <a href='mailto:laura.beggel@web.de'>laura.beggel@web.de</a> (<a href='https://orcid.org/0000-0002-8872-8535'>ORCID</a>) [contributor]</li>
<li>Quay Au <a href='mailto:quay.au@stat.uni-muenchen.de'>quay.au@stat.uni-muenchen.de</a> (<a href='https://orcid.org/0000-0002-5252-8902'>ORCID</a>) [contributor]</li>
<li>Martin Binder <a href='mailto:ma.binder@campus.lmu.de'>ma.binder@campus.lmu.de</a> [contributor]</li>
<li>Florian Pfisterer <a href='mailto:pfistererf@googlemail.com'>pfistererf@googlemail.com</a> [contributor]</li>
<li>Stefan Coors <a href='mailto:stefan.coors@gmx.net'>stefan.coors@gmx.net</a> [contributor]</li>
<li>Steve Bronder <a href='mailto:sab2287@columbia.edu'>sab2287@columbia.edu</a> [contributor]</li>
<li>Alexander Engelhardt <a href='mailto:alexander.w.engelhardt@gmail.com'>alexander.w.engelhardt@gmail.com</a> [contributor]</li>
<li>Christoph Molnar <a href='mailto:christoph.molnar@stat.uni-muenchen.de'>christoph.molnar@stat.uni-muenchen.de</a> [contributor]</li>
<li>Annette Spooner <a href='mailto:a.spooner@unsw.edu.au'>a.spooner@unsw.edu.au</a> [contributor]</li>
</ul>

mlr: Machine Learning in R

mlr-package: mlr: Machine Learning in R

Description

Arguments

Author

See Also