mlpack - Questions

I found a bug in the code and/or documentation. How do I report it?

Please make a small and self-contained program that exposes the bug, and then open an issue at the Github repo. Issue templates are available to help with the bug report process. You can also use one of the chat channels.

How do I cite mlpack in my work?

Please cite the following paper if you use mlpack in your work. Citations are useful for the continued development of the library.

R.R. Curtin, M. Edel, O. Shrit, S. Agrawal, S. Basak, J.J. Balamuta, R. Birmingham, K. Dutt, D. Eddelbuettel, R. Garg, S. Jaiswal, A. Kaushik, S.Kim, A. Mukherjee, N.G. Sai, N. Sharma, Y.S. Parihar, R. Swain, and C. Sanderson. "mlpack 4: a fast, header-only C++ machine learning library." Journal of Open Source Software 8:82, 2023. [bibtex]

What is the distribution license for mlpack?

mlpack is licensed under the permissive 3-clause BSD license. See also a Quick Summary of the license.

Who are the developers?

mlpack is a community-led effort. mlpack uses an open governance model and is fiscally sponsored by NumFOCUS. Consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs. See the community page for more details and a list of contributors.

What are the development goals?

See the vision document, which lays out a number of development goals and directions for mlpack in the short- to medium-term future.

Where is the source code?

mlpack development is done on GitHub and the source code is available there. There are a few related repositories that might be worth checking out also:

• ensmallen: numerical optimization library
• examples: simple examples of mlpack usage
• models: additional implementations of machine learning models

Do you accept contributions?

Contributions are absolutely welcome for mlpack, and anyone is welcome to participate and contribute. See the community page for more details.

Is there a real-time chat channel?

The mlpack community uses Matrix, in the room #mlpack:matrix.org. You will need to set up a matrix.org account and use a client such as Element or others.

A Slack workspace is also available at mlpack.slack.com; in order to create an account, you'll need to use the auto-inviter to send yourself an invite: slack-inviter.mlpack.org:4000. Note that the Slack channel is a bridged version of the Matrix channel, and it is generally a better experience to use Matrix.