mlpack is a "machine learning" C++ library. Most specifically, it contains all kinds of basic large data analysis tools, such as clustering algorithms (knn, kmeans, dbscan), lots of large graph algorithms, and various related learning models (neural networks, autoencoders, markov and bayes models)...
Most of that community use python tools, so the library is about 3 times as fast as those, usually. mlpack features command-line programs, as well as python bindings (took me a bit of work to get the python stuff just right). Most of the included patches have been discussed with upstream, and will likely vanish when upgrade time comes. Shorter descr for mlpack: mlpack is a fast, flexible machine learning library, written in C++, that aims to provide fast, extensible implementations of cutting-edge machine learning algorithms. armadillo is a C++ wrapper around lapack/blas linear algebra libraries, a required dependency of mlpack. Armadillo is a linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use. Provides high-level syntax and functionality deliberately similar to Matlab Attached is a tarball for math/mlpack and math/armadillo (extract under ports) I haven't checked that it builds under anything but amd64, though it should with a proper C++ compiler (hence the compiler annotations). Not sure it makes a lot of sense though, as the datasets for which mlpack make sense will usually take >16GB memory space...
mlpack.tgz
Description: mlpack-3.0.3.tgz
