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mlr: Machine Learning in R

Bischl, Bernd and Lang, Michel and Kotthoff, Lars and Schiffner, Julia and Richter, Jajob and Studerus, Erich and Casalicchio, Giuseppe and Jones, Zachary M.. (2016) mlr: Machine Learning in R. Journal of machine learning research, 17. pp. 1-5.

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Official URL: https://edoc.unibas.ch/70700/

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Abstract

The MLR package provides a generic, object-oriented, and extensible framework for classification, regression, survival analysis and clustering for the R language. It provides a unified interface to more than 160 basic learners and includes meta-algorithms and model selection techniques to improve and extend the functionality of basic learners with, e.g., hyperpa-rameter tuning, feature selection, and ensemble construction. Parallel high-performance computing is natively supported. The package targets practitioners who want to quickly apply machine learning algorithms, as well as researchers who want to implement, benchmark, and compare their new methods in a structured environment.
Faculties and Departments:03 Faculty of Medicine
03 Faculty of Medicine > Bereich Psychiatrie (Klinik)
03 Faculty of Medicine > Departement Klinische Forschung > Bereich Psychiatrie (Klinik)
03 Faculty of Medicine > Bereich Psychiatrie (Klinik) > Erwachsenenpsychiatrie UPK
03 Faculty of Medicine > Departement Klinische Forschung > Bereich Psychiatrie (Klinik) > Erwachsenenpsychiatrie UPK
03 Faculty of Medicine > Bereich Psychiatrie (Klinik) > Erwachsenenpsychiatrie UPK > Erwachsenenpsychiatrie (Riecher-Rössler)
03 Faculty of Medicine > Departement Klinische Forschung > Bereich Psychiatrie (Klinik) > Erwachsenenpsychiatrie UPK > Erwachsenenpsychiatrie (Riecher-Rössler)
UniBasel Contributors:Studerus, Erich
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Microtome Publishing
ISSN:1532-4435
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:03 Jul 2020 08:27
Deposited On:03 Jul 2020 08:27

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