# mlr3

> mlr3: Machine Learning in R - next generation

**Wikidata**: [Q120703067](https://www.wikidata.org/wiki/Q120703067)  
**Source**: https://4ort.xyz/entity/mlr3

## Summary
mlr3 is a modern, object-oriented machine learning framework for R, designed as the next generation of machine learning tools in the R ecosystem. It is distributed as free software under open-source terms, allowing users to freely run, study, modify, and distribute it.

## Key Facts
- **Instance of**: Free software and R package
- **Programming language**: R
- **First release**: Version 0.1.1 on July 25, 2019
- **Latest release**: Version 0.4.0 on July 22, 2020
- **Website**: [https://mlr3.mlr-org.com/](https://mlr3.mlr-org.com/)
- **Source code repository**: [https://github.com/mlr-org/mlr3](https://github.com/mlr-org/mlr3)
- **CRAN project**: mlr3
- **MacPorts port**: R-mlr3
- **Described by source**: "mlr3: A modern object-oriented machine learning framework in R"

## FAQs
### Q: What is mlr3, and what does it do?
A: mlr3 is a next-generation machine learning framework for R, designed to provide a modern, object-oriented approach to machine learning tasks. It is distributed as free software, allowing users to freely run, study, modify, and distribute it.

### Q: Who developed mlr3, and when was it first released?
A: mlr3 was developed by the mlr-org community, and its first version (0.1.1) was released on July 25, 2019. The latest version as of the provided data is 0.4.0, released on July 22, 2020.

### Q: Is mlr3 open-source?
A: Yes, mlr3 is distributed as free software under open-source terms, allowing users to freely run, study, modify, and distribute it.

### Q: Where can I find the source code for mlr3?
A: The source code for mlr3 is available on GitHub at [https://github.com/mlr-org/mlr3](https://github.com/mlr-org/mlr3).

### Q: How do I install mlr3?
A: mlr3 can be installed from the Comprehensive R Archive Network (CRAN) using the command `install.packages("mlr3")` in R. It is also available via MacPorts as `R-mlr3`.

## Why It Matters
mlr3 represents a significant advancement in the R ecosystem for machine learning, offering a modern, object-oriented framework that addresses the limitations of earlier versions. By providing a more structured and extensible approach, mlr3 simplifies the process of developing and deploying machine learning models. Its open-source nature ensures accessibility and community-driven development, making it a valuable tool for researchers and practitioners alike. The framework's focus on modularity and interoperability with other R packages enhances its utility in various machine learning workflows. As the field of machine learning continues to evolve, mlr3 plays a crucial role in bridging the gap between traditional statistical analysis and cutting-edge machine learning techniques.

## Notable For
- **Modern framework**: mlr3 is designed as the next generation of machine learning tools in R, offering a more structured and object-oriented approach compared to earlier versions.
- **Open-source**: Distributed under free software terms, allowing users to freely run, study, modify, and distribute it.
- **Community-driven**: Developed by the mlr-org community, ensuring continuous updates and improvements.
- **CRAN availability**: Available on the Comprehensive R Archive Network (CRAN), making it easily accessible to R users.
- **MacPorts support**: Also available via MacPorts as `R-mlr3`, expanding its reach across different platforms.

## Body
### Overview
mlr3 is a machine learning framework for R, positioned as the next generation of tools in the R ecosystem. It is designed to address the limitations of earlier versions by providing a more modern, object-oriented approach to machine learning tasks.

### Development and Releases
- **First release**: Version 0.1.1 was released on July 25, 2019.
- **Latest release**: Version 0.4.0 was released on July 22, 2020.
- **Development**: The framework is developed by the mlr-org community, with releases documented on GitHub.

### Availability and Installation
- **CRAN**: mlr3 is available on the Comprehensive R Archive Network (CRAN) under the project name `mlr3`.
- **MacPorts**: It is also available via MacPorts as `R-mlr3`.
- **Source code**: The source code is hosted on GitHub at [https://github.com/mlr-org/mlr3](https://github.com/mlr-org/mlr3).

### Key Features
- **Object-oriented design**: mlr3 is built with a modern, object-oriented approach, enhancing its modularity and extensibility.
- **Free software**: Distributed under open-source terms, allowing users to freely run, study, modify, and distribute it.
- **Community-driven**: Developed by the mlr-org community, ensuring continuous updates and improvements.

### Significance
mlr3 plays a crucial role in the R ecosystem by providing a more structured and extensible approach to machine learning. Its open-source nature and community-driven development make it a valuable tool for researchers and practitioners. The framework's focus on modularity and interoperability enhances its utility in various machine learning workflows.

## References

1. [2025](https://github.com/EvanLi/Github-Ranking/blob/master/Data/github-ranking-2025-07-06.csv)
2. [Release 0.1.1. 2019](https://github.com/mlr-org/mlr3/releases/tag/v0.1.1)
3. [Release 0.1.2. 2019](https://github.com/mlr-org/mlr3/releases/tag/v0.1.2)
4. [Release 0.1.3. 2019](https://github.com/mlr-org/mlr3/releases/tag/v0.1.3)
5. [Release 0.1.4. 2019](https://github.com/mlr-org/mlr3/releases/tag/v0.1.4)
6. [Release 0.1.5. 2019](https://github.com/mlr-org/mlr3/releases/tag/v0.1.5)
7. [Release 0.1.6. 2019](https://github.com/mlr-org/mlr3/releases/tag/v0.1.6)
8. [Release 0.1.7. 2020](https://github.com/mlr-org/mlr3/releases/tag/v0.1.7)
9. [Release 0.1.8. 2020](https://github.com/mlr-org/mlr3/releases/tag/v0.1.8)
10. [Release 0.3.0. 2020](https://github.com/mlr-org/mlr3/releases/tag/v0.3.0)
11. [Release 0.4.0. 2020](https://github.com/mlr-org/mlr3/releases/tag/v0.4.0)
12. [Release 0.5.0. 2020](https://github.com/mlr-org/mlr3/releases/tag/v0.5.0)
13. [Release 0.6.0. 2020](https://github.com/mlr-org/mlr3/releases/tag/v0.6.0)
14. [Release 0.7.0. 2020](https://github.com/mlr-org/mlr3/releases/tag/v0.7.0)
15. [Release 0.8.0. 2020](https://github.com/mlr-org/mlr3/releases/tag/v0.8.0)
16. [Release 0.9.0. 2020](https://github.com/mlr-org/mlr3/releases/tag/v0.9.0)
17. [Release 0.10.0. 2021](https://github.com/mlr-org/mlr3/releases/tag/v0.10.0)
18. [Release 0.11.0. 2021](https://github.com/mlr-org/mlr3/releases/tag/v0.11.0)
19. [Release 0.12.0. 2021](https://github.com/mlr-org/mlr3/releases/tag/v0.12.0)
20. [Release 0.13.0. 2021](https://github.com/mlr-org/mlr3/releases/tag/v0.13.0)
21. [Release 0.13.1. 2022](https://github.com/mlr-org/mlr3/releases/tag/v0.13.1)
22. [Release 0.13.2. 2022](https://github.com/mlr-org/mlr3/releases/tag/v0.13.2)
23. [Release 0.13.3. 2022](https://github.com/mlr-org/mlr3/releases/tag/v0.13.3)
24. [Release 0.13.4. 2022](https://github.com/mlr-org/mlr3/releases/tag/v0.13.4)
25. [Release 0.14.0. 2022](https://github.com/mlr-org/mlr3/releases/tag/v0.14.0)
26. [Release 0.14.1. 2022](https://github.com/mlr-org/mlr3/releases/tag/v0.14.1)
27. [Release 0.15.0. 2023](https://github.com/mlr-org/mlr3/releases/tag/v0.15.0)
28. [Release 0.16.0. 2023](https://github.com/mlr-org/mlr3/releases/tag/v0.16.0)
29. [Release 0.16.1. 2023](https://github.com/mlr-org/mlr3/releases/tag/v0.16.1)
30. [Release 0.17.0. 2023](https://github.com/mlr-org/mlr3/releases/tag/v0.17.0)
31. [Release 0.17.1. 2023](https://github.com/mlr-org/mlr3/releases/tag/v0.17.1)
32. [Release 0.17.2. 2024](https://github.com/mlr-org/mlr3/releases/tag/v0.17.2)
33. [Release 0.18.0. 2024](https://github.com/mlr-org/mlr3/releases/tag/v0.18.0)
34. [Release 0.19.0. 2024](https://github.com/mlr-org/mlr3/releases/tag/v0.19.0)
35. [Release 0.20.0. 2024](https://github.com/mlr-org/mlr3/releases/tag/v0.20.0)
36. [Release 0.20.1. 2024](https://github.com/mlr-org/mlr3/releases/tag/v0.20.1)
37. [Release 0.20.2. 2024](https://github.com/mlr-org/mlr3/releases/tag/v0.20.2)
38. [Release 0.21.0. 2024](https://github.com/mlr-org/mlr3/releases/tag/v0.21.0)
39. [Release 0.21.1. 2024](https://github.com/mlr-org/mlr3/releases/tag/v0.21.1)
40. [Release 0.22.0. 2024](https://github.com/mlr-org/mlr3/releases/tag/v0.22.0)
41. [Release 0.22.1. 2024](https://github.com/mlr-org/mlr3/releases/tag/v0.22.1)
42. [Release 0.23.0. 2025](https://github.com/mlr-org/mlr3/releases/tag/v0.23.0)
43. [Release 1.0.0. 2025](https://github.com/mlr-org/mlr3/releases/tag/v1.0.0)
44. [Release 1.0.1. 2025](https://github.com/mlr-org/mlr3/releases/tag/v1.0.1)
45. [Release 1.1.0. 2025](https://github.com/mlr-org/mlr3/releases/tag/v1.1.0)
46. [Release 1.2.0. 2025](https://github.com/mlr-org/mlr3/releases/tag/v1.2.0)
47. [Release 1.3.0. 2025](https://github.com/mlr-org/mlr3/releases/tag/v1.3.0)
48. [Release 1.4.0. 2026](https://github.com/mlr-org/mlr3/releases/tag/v1.4.0)
49. [Release 1.5.0. 2026](https://github.com/mlr-org/mlr3/releases/tag/v1.5.0)
50. [Release 1.6.0. 2026](https://github.com/mlr-org/mlr3/releases/tag/v1.6.0)