Citation

mlpack uses as open governance model and is fiscally sponsored by NumFOCUS. Please cite the following paper if you use mlpack in your work. Citations are useful for the continued development of the library.

mlpack 3: a fast, flexible machine learning library.  R.R. Curtin, M. Edel, M. Lozhnikov, Y. Mentekidis, S. Ghaisas, S. Zhang. Journal of Open Source Software 3:26, 2018.     

Below are some additional relevant publications about mlpack.

mlpack open-source machine learning library and community  M. Edel. NeurIPS 2018 MLOSS Workshop, 2018.     

mlpack: a scalable C++ machine learning library  R.R. Curtin, J.R. Cline, N.P. Slagle, W.B. March, P. Ram, N.A. Mehta, A.G. Gray,The Journal of Machine Learning Research (JMLR), vol. 14, p. 801-805, 2013.     

mlpack: a scalable C++ machine learning library  R.R. Curtin, J.R. Cline, N.P. Slagle, M.L. Amidon, A.G. Gray. NIPS 2011 Workshop on Big Learning, Granada, Spain, 2011.     

License

mlpack is open source software, licensed under the permissive 3-clause BSD license.

Benchmarks

We developed a benchmarking system (An automatic benchmarking system, M. Edel, A. Soni, R.R. Curtin) that runs benchmarks for the various algorithms implemented in mlpack. When applicable, timing results are also given for other libraries. mlpack is quite fast, with benchmarks showing mlpack out- performing other libraries' implementations of the same methods.

Several randomly generated, uniformly distributed datasets of varying sizes were used for this benchmark. The computation time of k-NN with k=5 for each library and each dataset size is given in Table.