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Facts
| Fact | szilard/benchm-ml A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.). | mlr-org/mlr3 mlr3: Machine Learning in R - next generation |
|---|---|---|
| Stars | 1,896 | 1,083 |
| Net stars, last 30 days | 0 | +3 |
| Largest star day | +1 on Jun 5, 2026 | +2 on Aug 4, 2026 |
| Milestone reached in the record | None | None |
| Forks | 326 | 98 |
| Language | R | R |
| License | MIT | LGPL-3.0 |
| Created | Mar 28, 2015 | Aug 26, 2018 |
| Last push | Sep 16, 2022 | Oct 30, 2026 |
| Archived | No | No |
| Health facts: Maintenance | 1 of 4 checks (2 without data) | 2 of 4 checks (2 without data) |
| Health facts: Releases | 0 of 3 checks (2 without data) | 2 of 3 checks (1 without data) |
| Health facts: Security practice | 0 of 1 check (1 without data) | 0 of 1 check (1 without data) |
| Health facts: Community files | 1 of 3 checks (2 without data) | 1 of 3 checks (2 without data) |
| Commits, last 13 weeks | No data | No data |
| Weeks with commits, last 52 | No data | No data |
| In the Repository Index since | Oct 22, 2026 | Oct 22, 2026 |
Topics that all of them have on the Repository Host: machine-learning, data-science, r. The facts come from the Repository Host and from the Star History that AwesomeRepos records. A shared topic does not mean that one repository can replace another. Each Health Facts row is one dimension alone. AwesomeRepos does not add them into one score. How each check is defined