mlpack (Machine Learning PACK) is an open-source, intuitive, fast, and scalable C++ machine learning library, meant to be a machine learning analog to LAPACK. It aims to implement a wide array of machine learning methods and function as a "swiss army knife" for machine learning researchers.
This Trac install is meant to manage bug reports, feature requests, mlpack documentation, and other general development-related tasks. The links at the top of the page should provide a good place to start; TracGuide contains basic built-in Trac documentation.
To check out current sources from subversion anonymously (having trouble? see KnownSVNIssues):
$ svn co http://svn.cc.gatech.edu/fastlab/mlpack/trunk/
mlpack depends on the following libraries:
- Armadillo >= 3.6.0
- LibXml2 >= 2.6.0
- Boost - program_options, math_c99, unit_test_framework, random
All of these should be available in your distribution's package manager.
- UsingCMake -- Tutorial for using/modifying our CMake configuration.
- MLPACKOnWindows -- Tutorial for compiling MLPACK on Windows.
- NewStyleGuidelines -- Coding style guidelines followed in mlpack code.
- The Future Of mlpack -- mlpack design goals document (from 2009).
- Armadillo -- Project website for Armadillo; includes documentation.
- Jenkins -- mlpack build server.
- CompetingLibraries -- Information about competing libraries.
- ReleasePreparationGuide -- List of tasks to be done when releasing MLPACK.
- JenkinsSlaveConfiguration -- How to set up a slave for the build server.
- SummerOfCodeIdeas -- List of ideas for Google Summer of Code 2014.
- JenkinsUsers -- Notes on Jenkins user configuration.
- AutomaticBenchmark -- Notes regarding the automatic benchmark system.