mlpack is a C++ machine learning library with 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. mlpack outperforms competing machine learning libraries by large margins; see the BigLearning workshop paper for details.
mlpack is developed by the fundamental algorithmic and statistical tools laboratory (FASTLab) at Georgia Tech. It is released free of charge, under the GNU Lesser General Public License (LGPL) version 3.
mlpack was presented at the BigLearning workshop of NIPS 2011 [pdf]. Please cite mlpack in your work using this citation.
Contributors include:
- Ryan Curtin
- James Cline
- Neil Slagle
- Matthew Amidon
- Sterling Peet
- Vlad Grantcharov
- Ajinkya Kale
- Bill March
- Dongryeol Lee
- Nishant Mehta
- Parikshit Ram
- Rajendran Mohan
- Trironk Kiatkungwanglai
- Patrick Mason
- Chip Mappus
- Hua Ouyang
- Tran Quoc Long
- Noah Kauffman
- Guillermo Colon
- Wei Guan
- Ryan Riegel
- Nikolaos Vasiloglou
- Garry Boyer
- Andreas Löf
- Marcus Edel