| mlr: Machine Learning in R B Bischl, M Lang, L Kotthoff, J Schiffner, J Richter, E Studerus, ... The Journal of Machine Learning Research 17 (1), 5938-5942, 2016 | 487 | 2016 |
| mlrMBO: A modular framework for model-based optimization of expensive black-box functions B Bischl, J Richter, J Bossek, D Horn, J Thomas, M Lang arXiv preprint arXiv:1703.03373, 2017 | 103 | 2017 |
| Benchmark for filter methods for feature selection in high-dimensional classification data A Bommert, X Sun, B Bischl, J Rahnenführer, M Lang Computational Statistics & Data Analysis 143, 106839, 2020 | 82 | 2020 |
| BatchJobs and BatchExperiments: Abstraction mechanisms for using R in batch environments B Bischl, M Lang, O Mersmann, J Rahnenführer, C Weihs Journal of Statistical Software 64 (i11), 2015 | 63 | 2015 |
| batchtools: Tools for R to work on batch systems M Lang, B Bischl, D Surmann The Journal of Open Source Software 2 (10), 2017 | 56 | 2017 |
| OpenML benchmarking suites and the OpenML100 B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ... stat 1050, 11, 2017 | 45* | 2017 |
| OpenML: An R package to connect to the machine learning platform OpenML G Casalicchio, J Bossek, M Lang, D Kirchhoff, P Kerschke, B Hofner, ... Computational Statistics 34 (3), 977-991, 2019 | 35 | 2019 |
| Automatic model selection for high-dimensional survival analysis M Lang, H Kotthaus, P Marwedel, C Weihs, J Rahnenführer, B Bischl Journal of Statistical Computation and Simulation 85 (1), 62-76, 2015 | 35 | 2015 |
| Package ‘data. table’ M Dowle, A Srinivasan, J Gorecki, M Chirico, P Stetsenko, T Short, ... Extension of ‘data. frame, 2019 | 30 | 2019 |
| Survival models with preclustered gene groups as covariates K Kammers, M Lang, JG Hengstler, M Schmidt, J Rahnenführer BMC bioinformatics 12 (1), 1-12, 2011 | 30 | 2011 |
| parallelMap: Unified interface to parallelization back-ends B Bischl, M Lang R package version 1, 2015 | 26 | 2015 |
| BiocParallel: Bioconductor facilities for parallel evaluation M Morgan, V Obenchain, M Lang, R Thompson, N Turaga R package version 1 (1), 2014 | 26 | 2014 |
| mlr3: A modern object-oriented machine learning framework in R M Lang, M Binder, J Richter, P Schratz, F Pfisterer, S Coors, Q Au, ... Journal of Open Source Software 4 (44), 1903, 2019 | 19 | 2019 |
| Runtime and memory consumption analyses for machine learning R programs H Kotthaus, I Korb, M Lang, B Bischl, J Rahnenführer, P Marwedel Journal of Statistical Computation and Simulation 85 (1), 14-29, 2015 | 18 | 2015 |
| Computing on high performance clusters with R: Packages BatchJobs and BatchExperiments B Bischl, M Lang, O Mersmann, J Rahnenfuehrer, C Weihs | 18 | 2012 |
| mlr: Machine Learning in R., 2013 B Bischl, M Lang, L Kotthoff, J Schiffner, J Richter, Z Jones, G Casalicchio, ... R package version 2, 0 | 15 | |
| checkmate: fast argument checks for Defensive R programming M Lang arXiv preprint arXiv:1701.04781, 2017 | 14 | 2017 |
| A multicriteria approach to find predictive and sparse models with stable feature selection for high-dimensional data A Bommert, J Rahnenführer, M Lang Computational and mathematical methods in medicine 2017, 2017 | 13 | 2017 |
| Faster model-based optimization through resource-aware scheduling strategies J Richter, H Kotthaus, B Bischl, P Marwedel, J Rahnenführer, M Lang International Conference on Learning and Intelligent Optimization, 267-273, 2016 | 12 | 2016 |
| mlr: Machine Learning in R. R package version 2.9 B Bischl, M Lang, J Richter, J Bossek, L Judt, T Kuehn, E Studerus, ... | 12 | 2015 |
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de
