mlpack

mlpack
Initial releaseFebruary 1, 2008; 16 years ago (2008-02-01)[1]
Stable release
4.3.0[2] / 27 November 2023; 4 months ago (27 November 2023)
Repository
  • github.com/mlpack/mlpack
Written inC++, Python, Julia, Go
Operating systemCross-platform
Available inEnglish
TypeSoftware library Machine learning
LicenseOpen source (BSD)
Websitemlpack.org 

mlpack is a machine learning software library for C++, built on top of the Armadillo library and the ensmallen numerical optimization library.[3] mlpack has an emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum flexibility for expert users.[4] Its intended target users are scientists and engineers.

It is open-source software distributed under the BSD license, making it useful for developing both open source and proprietary software. Releases 1.0.11 and before were released under the LGPL license. The project is supported by the Georgia Institute of Technology and contributions from around the world.

Miscellaneous features

Class templates for GRU, LSTM structures are available, thus the library also supports Recurrent Neural Networks.[citation needed]

There are bindings to R, Go, Julia,[5] and Python. Its binding system is extensible to other languages.

Supported algorithms

Currently mlpack supports the following algorithms and models:

See also

References

  1. ^ "Initial checkin of the regression package to be released · mlpack/mlpack". February 8, 2008. Retrieved May 24, 2020.
  2. ^ "Release 4.3.0". 27 November 2023. Retrieved 19 December 2023.
  3. ^ Ryan Curtin; et al. (2021). "The ensmallen library for flexible numerical optimization". Journal of Machine Learning Research. 22 (166): 1–6. arXiv:2108.12981. Bibcode:2021arXiv210812981C.
  4. ^ Ryan Curtin; et al. (2023). "mlpack 4: a fast, header-only C++ machine learning library". Journal of Open Source Software. 8 (82): 5026. arXiv:2302.00820.
  5. ^ "Mlpack/Mlpack.jl". 10 June 2021.

External links

  • Official website
  • mlpack on GitHub
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