mlr
| swMATH ID: | 12357 |
| Software Authors: | Bischl, B.; Wornowizki, M.; Borg, K. |
| Description: | mlr: Machine Learning in R. 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. |
| Homepage: | http://cran.r-project.org/web/packages/mlr/index.html |
| Source Code: |
 https://github.com/cran/mlr
|
| Dependencies: | R |
| Related Software: | R; caret; Scikit; ranger; randomForest; rpart; mlr3; Kernlab; UCI-ml; OpenML; glmnet; e1071; WEKA; GitHub; ggplot2; mlrMBO; kknn; BatchJobs; CRAN; batchtools |
| Cited in: | 25 Documents |
Standard Articles
| 1 Publication describing the Software, including 1 Publication in zbMATH | Year |
|---|---|
|
mlr: machine learning in \(\mathbf R\). Zbl 1392.68007 Bischl, Bernd; Lang, Michel; Kotthoff, Lars; Schiffner, Julia; Richter, Jakob; Studerus, Erich; Casalicchio, Giuseppe; Jones, Zachary M. |
2016
|
all
top 5
Cited by 84 Authors
all
top 5
Cited in 14 Serials
all
top 5
