mlr3: Machine Learning in R - Next Generation

Canonical link: https://rscholar.com/pkg/mlr3

Michel Lang • Bernd Bischl • Jakob Richter • Patrick Schratz • Giuseppe Casalicchio • Stefan Coors • Quay Au • Martin Binder • Florian Pfisterer • Raphael Sonabend • Lennart Schneider • Marc Becker • Sebastian Fischer • Lona Koers • View description and downloads View dependencies GitHub project

2019 Published

0.21.1 Version

0 Citations

14 Authors

Referenced by ⇅	Year
NADIA: NA Data Imputation Algorithms (Version 0.4.2)	2020
BioM2: Biologically Explainable Machine Learning Framework (Version 1.1.0)	2023
DALEXtra: Extension for 'DALEX' Package (Version 2.3.0)	2019
DoubleML: Double Machine Learning in R (Version 1.0.1)	2020
FACT: Feature Attributions for ClusTering (Version 0.1.1)	2023
GenericML: Generic Machine Learning Inference (Version 0.2.2)	2021
MantaID: A Machine-Learning Based Tool to Automate the Identification of Biological Database IDs (Version 1.0.4)	2022
condvis2: Interactive Conditional Visualization for Supervised and Unsupervised Models in Shiny (Version 0.1.2)	2019
counterfactuals: Counterfactual Explanations (Version 0.1.6)	2023
cpi: Conditional Predictive Impact (Version 0.1.4)	2022
drape: Doubly Robust Average Partial Effects (Version 0.0.1)	2023
explainer: Machine Learning Model Explainer (Version 1.0.2)	2023
gKRLS: Generalized Kernel Regularized Least Squares (Version 1.0.4)	2023
highMLR: Feature Selection for High Dimensional Survival Data (Version 0.1.1)	2021
iml: Interpretable Machine Learning (Version 0.11.3)	2018
mcboost: Multi-Calibration Boosting (Version 0.4.3)	2021
miesmuschel: Mixed Integer Evolution Strategies (Version 0.0.4-2)	2022
mlr3batchmark: Batch Experiments for 'mlr3' (Version 0.1.1)	2023
mlr3benchmark: Analysis and Visualisation of Benchmark Experiments (Version 0.1.6)	2020
mlr3data: Collection of Machine Learning Data Sets for 'mlr3' (Version 0.9.0)	2020
mlr3cluster: Cluster Extension for 'mlr3' (Version 0.1.10)	2020
mlr3fairness: Fairness Auditing and Debiasing for 'mlr3' (Version 0.3.2)	2022
mlr3db: Data Base Backend for 'mlr3' (Version 0.5.2)	2019
mlr3filters: Filter Based Feature Selection for 'mlr3' (Version 0.8.1)	2019
mlr3fda: Extending 'mlr3' to Functional Data Analysis (Version 0.2.0)	2024
mlr3fselect: Feature Selection for 'mlr3' (Version 1.2.1)	2020
mlr3hyperband: Hyperband for 'mlr3' (Version 0.6.0)	2020
mlr3learners: Recommended Learners for 'mlr3' (Version 0.8.0)	2019
mlr3mbo: Flexible Bayesian Optimization (Version 0.2.6)	2022
mlr3oml: Connector Between 'mlr3' and 'OpenML' (Version 0.10.0)	2020
mlr3resampling: Resampling Algorithms for 'mlr3' Framework (Version 2024.9.6)	2023
mlr3pipelines: Preprocessing Operators and Pipelines for 'mlr3' (Version 0.7.0)	2019
mlr3shiny: Machine Learning in 'shiny' with 'mlr3' (Version 0.3.0)	2020
mlr3spatial: Support for Spatial Objects Within the 'mlr3' Ecosystem (Version 0.5.0)	2021
mlr3spatiotempcv: Spatiotemporal Resampling Methods for 'mlr3' (Version 2.3.1)	2020
mlr3summary: Model and Learner Summaries for 'mlr3' (Version 0.1.0)	2024
mlr3superlearner: Super Learner Fitting and Prediction (Version 0.1.2)	2024
mlr3torch: Deep Learning with 'mlr3' (Version 0.1.2)	2024
mlr3tuning: Hyperparameter Optimization for 'mlr3' (Version 1.2.0)	2019
mlr3tuningspaces: Search Spaces for 'mlr3' (Version 0.5.1)	2021
mlr3verse: Easily Install and Load the 'mlr3' Package Family (Version 0.3.0)	2019
mlr3viz: Visualizations for 'mlr3' (Version 0.10.0)	2020
mlrintermbo: Model-Based Optimization for 'mlr3' Through 'mlrMBO' (Version 0.5.1-1)	2021
sense: Automatic Stacked Ensemble for Regression Tasks (Version 1.1.0)	2021
spFSR: Feature Selection and Ranking via Simultaneous Perturbation Stochastic Approximation (Version 2.0.4)	2018
vetiver: Version, Share, Deploy, and Monitor Models (Version 0.2.5)	2021
vip: Variable Importance Plots (Version 0.4.1)	2018
vivid: Variable Importance and Variable Interaction Displays (Version 0.2.9)	2021

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