The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

Please cite both the package and the original articles / software in your publications:

Mouselimis L, Fukatani R, Titov N, Zhang T, Johnson R (2022). RGF: Regularized Greedy Forest. R package version 1.1.1, https://CRAN.R-project.org/package=RGF.

Fukatani R, Titov N, Zhang T, Johnson R (2022). rgf_python: The wrapper of machine learning algorithm Regularized Greedy Forest (RGF) for Python. https://pypi.org/project/rgf-python/.

Johnson R, Zhang T (2014). “Learning Nonlinear Functions Using Regularized Greedy Forest.” IEEE Transactions on Pattern Analysis and Machine Intelligence, 36, 942–954. doi:10.1109/TPAMI.2013.159.

Johnson R, Zhang T (2011). “Learning Nonlinear Functions Using Regularized Greedy Forest.” arXiv.org, stat.ML. arXiv:1109.0887.

Corresponding BibTeX entries:

  @Manual{,
    title = {{RGF}: Regularized Greedy Forest},
    author = {Lampros Mouselimis and Ryosuke Fukatani and Nikita Titov
      and Tong Zhang and Rie Johnson},
    year = {2022},
    note = {R package version 1.1.1},
    url = {https://CRAN.R-project.org/package=RGF},
  }
  @Manual{,
    title = {{rgf_python}: The wrapper of machine learning algorithm
      Regularized Greedy Forest (RGF) for Python},
    author = {Ryosuke Fukatani and Nikita Titov and Tong Zhang and Rie
      Johnson},
    year = {2022},
    url = {https://pypi.org/project/rgf-python/},
  }
  @Article{,
    title = {Learning Nonlinear Functions Using Regularized Greedy
      Forest},
    author = {Rie Johnson and Tong Zhang},
    journal = {IEEE Transactions on Pattern Analysis and Machine
      Intelligence},
    year = {2014},
    volume = {36},
    pages = {942--954},
    doi = {10.1109/TPAMI.2013.159},
  }
  @Article{,
    title = {Learning Nonlinear Functions Using Regularized Greedy
      Forest},
    author = {Rie Johnson and Tong Zhang},
    journal = {arXiv.org, stat.ML},
    year = {2011},
    note = {arXiv:1109.0887},
  }

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.