The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Bischl B, Lang M, Kotthoff L, Schiffner J, Richter J, Studerus E, Casalicchio G, Jones Z (2016). “mlr: Machine Learning in R.” Journal of Machine Learning Research, 17(170), 1-5. https://jmlr.org/papers/v17/15-066.html.
Lang M, Kotthaus H, Marwedel P, Weihs C, Rahnenfuehrer J, Bischl B (2014). “Automatic model selection for high-dimensional survival analysis.” Journal of Statistical Computation and Simulation, 85(1), 62-76.
Bischl B, Kuehn T, Szepannek G (2016). “On Class Imbalance Correction for Classification Algorithms in Credit Scoring.” In Operations Research Proceedings 2014, 37-43. Springer.
Bischl B, Richter J, Bossek J, Horn D, Thomas J, Lang M (2017). “mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions.” arXiv preprint arXiv:1703.03373.
Probst P, Au Q, Casalicchio G, Stachl C, Bischl B (2017). “Multilabel Classification with R Package mlr.” arXiv preprint arXiv:1703.08991.
Casalicchio G, Bossek J, Lang M, Kirchhoff D, Kerschke P, Hofner B, Seibold H, Vanschoren J, Bischl B (2017). “OpenML: An R package to connect to the machine learning platform OpenML.” Computational Statistics, 1-15.
Corresponding BibTeX entries:
@Article{mlr, title = {{mlr}: Machine Learning in R}, author = {Bernd Bischl and Michel Lang and Lars Kotthoff and Julia Schiffner and Jakob Richter and Erich Studerus and Giuseppe Casalicchio and Zachary M. Jones}, journal = {Journal of Machine Learning Research}, year = {2016}, volume = {17}, number = {170}, pages = {1-5}, url = {https://jmlr.org/papers/v17/15-066.html}, }
@Article{automatic, title = {Automatic model selection for high-dimensional survival analysis}, author = {Michel Lang and Helena Kotthaus and Peter Marwedel and Claus Weihs and Joerg Rahnenfuehrer and Bernd Bischl}, journal = {Journal of Statistical Computation and Simulation}, year = {2014}, volume = {85}, number = {1}, pages = {62-76}, publisher = {Taylor & Francis}, }
@InCollection{bischl2016class, title = {On Class Imbalance Correction for Classification Algorithms in Credit Scoring}, author = {Bernd Bischl and Tobias Kuehn and Gero Szepannek}, booktitle = {Operations Research Proceedings 2014}, pages = {37-43}, year = {2016}, publisher = {Springer}, }
@Article{mlrmbo, title = {mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions}, author = {Bernd Bischl and Jakob Richter and Jakob Bossek and Daniel Horn and Janek Thomas and Michel Lang}, journal = {arXiv preprint arXiv:1703.03373}, year = {2017}, }
@Article{multilabel, title = {Multilabel Classification with R Package mlr}, author = {Philipp Probst and Quay Au and Giuseppe Casalicchio and Clemens Stachl and Bernd Bischl}, journal = {arXiv preprint arXiv:1703.08991}, year = {2017}, }
@Article{openml, title = {OpenML: An R package to connect to the machine learning platform OpenML}, author = {Giuseppe Casalicchio and Jakob Bossek and Michel Lang and Dominik Kirchhoff and Pascal Kerschke and Benjamin Hofner and Heidi Seibold and Joaquin Vanschoren and Bernd Bischl}, journal = {Computational Statistics}, pages = {1-15}, year = {2017}, publisher = {Springer}, }
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.