MLR3 Ecosystem ML Frameworks

Extension packages, learners, and resources built on the mlr3 machine learning framework for R. Includes specialized learners (probabilistic, survival, deep learning), fairness/inference tools, and official documentation. Does NOT include standalone ML frameworks, general R utilities, or non-mlr3-specific ML tools.

There are 50 mlr3 ecosystem frameworks tracked. 5 score above 50 (established tier). The highest-rated is GAA-UAM/scikit-fda at 66/100 with 340 stars and 82,254 monthly downloads. 1 of the top 10 are actively maintained.

Get all 50 projects as JSON

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#	Framework	Score	Tier	Stars	Language
1	GAA-UAM/scikit-fda Functional Data Analysis Python package	66	Established	340	Python
2	mlr-org/mlr3 mlr3: Machine Learning in R - next generation	58	Established	1,060	R
3	mlr-org/mlr3book Online version of Bischl, B., Sonabend, R., Kotthoff, L., & Lang, M. (Eds.)....	55	Established	276	TeX
4	mlr-org/mlr3extralearners Extra learners for use in mlr3.	53	Established	114	R
5	mlr-org/mlr3learners Recommended learners for mlr3	50	Established	97	R
6	naturalis/sdmdl Species Distribution Modelling using Deep Learning	47	Emerging	26	Python
7	mlr-org/mlr3proba Probabilistic Learning for mlr3	47	Emerging	147	R
8	mlr-org/mlr3tuning Hyperparameter optimization package of the mlr3 ecosystem	44	Emerging	59	R
9	stabgan/Linear-Discriminant-Analysis We used LDA in this project to expand the capabilities of our Logistic...	44	Emerging	9	Python
10	mlr-org/mlr3hyperband Successive Halving and Hyperband in the mlr3 ecosystem	43	Emerging	18	R
11	mlr-org/mlr3torch Deep learning framework for the mlr3 ecosystem based on torch	42	Emerging	55	R
12	mlr-org/mlr3misc Miscellaneous helper functions for mlr3	42	Emerging	13	R
13	mlr-org/mlr3verse Meta-package for installing/updating mlr3* packages.	41	Emerging	63	R
14	mlr-org/mlr3fda Functional Data Analysis for mlr3	41	Emerging	7	R
15	mlr-org/mlr3fselect Feature selection package of the mlr3 ecosystem.	41	Emerging	38	R
16	mingzehuang/latentcor latentcor is an R package provides estimation for latent correlation with...	37	Emerging	16	R
17	jo-phil/hopkins-statistic A Python package for computing the Hopkins statistic to assess clustering tendency.	37	Emerging	1	Python
18	Black-Swan-ICL/PyRKHSstats A Python package implementing a variety of statistical methods that rely on...	37	Emerging	16	Python
19	mlr-org/mlr3summary Model summaries for mlr3	36	Emerging	8	R
20	mlr-org/mlr3data Data sets used in the book, gallery, or in examples of mlr3.	36	Emerging	2	R
21	boyanangelov/sdmbench Benchmarking Species Distribution Models	36	Emerging	19	R
22	gcol33/corrselect R package for exhaustive selection of variable subsets below a correlation threshold.	35	Emerging	1	R
23	kapsner/mlsurvlrnrs Survival learners for the `mlexperiments` R 📦	34	Emerging	3	R
24	DaniloCVieira/iMESc This app is intended to dynamically integrate machine learning techniques to...	33	Emerging	10	R
25	Kaleidophon/deep-significance Enabling easy statistical significance testing for deep neural networks.	31	Emerging	339	Python
26	fabrice-rossi/mixvlmc Variable Length Markov Chains with Covariates	30	Emerging	6	R
27	canagnos/mcp Tools for Measuring Classification Performance for R, Python and Spark	29	Experimental	13	—
28	mlr-org/mlr3fairness mlr3 extension for Fairness in Machine Learning	27	Experimental	15	HTML
29	mlr-org/mlr3forecast Time series forecasting for mlr3	26	Experimental	7	R
30	nt-williams/mlr3superlearner Super learner fitting and prediction using mlr3	26	Experimental	11	R
31	bcgov/PEMprepr Machine Learning Predictive Ecosystem Mapping (MLPEM) data preparation	26	Experimental	5	R
32	pmsims-package/pmsims Simulation-based sample size tools for prediction models	25	Experimental	3	R
33	ModelOriented/hstats Friedman's H-statistics	25	Experimental	34	R
34	bcgov/PEMr Machine Learning Predictive Ecosystems Mapping (MLPEM)	24	Experimental	4	R
35	mlr-org/mlr3cmprsk Competing Risks Machine Learning for mlr3	24	Experimental	—	R
36	donishadsmith/vswift A R package for evaluating ML classification models.	23	Experimental	1	R
37	mlr-org/mlr3tuningspaces Collection of search spaces for hyperparameter optimization in the mlr3 ecosystem	23	Experimental	14	R
38	define957/SupportVectorLab Advanced Toolkit for Support Vector Machines in R	22	Experimental	4	R
39	Boris-Droz/PRODOM Tools for analysing fluorescence data using PARAFAC and Machine Learning (ML)	22	Experimental	—	R
40	CodingTigerTang/PrecisionRecallExplorer Interactive Shiny app for explaining precision–recall tradeoffs to business...	22	Experimental	—	R
41	Minoru938/KmdPlus This module contains a class for treating kernel mean descriptor (KMD), and...	21	Experimental	8	Jupyter Notebook
42	antoninschrab/mmdagg-paper Reproducibility code for MMD Aggregated Two-Sample Test, by Schrab, Kim,...	20	Experimental	17	Jupyter Notebook
43	mlr-org/mlr3inferr Statistical methods for inference on the generalization error	19	Experimental	5	R
44	shimenghuang/pycomets Algorithm-agnostic significance testing in supervised learning with multimodal data	19	Experimental	6	Python
45	Sulkysubject37/BioMoR BioMoR: Bioinformatics Modeling with Recursion and Autoencoder-Based...	15	Experimental	—	R
46	MALL-Lab/VIBES VIBES - VagInal Bacterial subtyping using machine learning for Enhanced...	13	Experimental	—	R
47	bcgov/PEMsamplr Construct standard sample plan for a machine-learning predictive ecosystem map	12	Experimental	3	R
48	bcgov/PEMmodelr Build a machine learning model for predictive ecosystem mapping	12	Experimental	3	R
49	LucasKook/comets Algorithm-agnostic significance testing in supervised learning with multimodal data	12	Experimental	10	R
50	luukka76/Feature-selection-method-based-on-entropy-and-similarity-R-codes R-codes for feature selection method that is based on fuzzy entropy and similarity	10	Experimental	1	R

Comparisons in this category

mlr3 and mlr3book (58 vs 55) mlr3 and mlr3proba (58 vs 47) mlr3 and mlr3extralearners (58 vs 53) mlr3 and mlr3learners (58 vs 50) mlr3 and mlr3verse (58 vs 41) mlr3 and mlr3torch (58 vs 42) mlr3 and mlr3misc (58 vs 42) mlr3 and mlr3summary (58 vs 36) mlr3 and mlr3fda (58 vs 41) mlr3extralearners and mlr3learners (53 vs 50)