libpca is a C++ library for principal component analysis and related transformations. It comes with example and unit tests. libpca is successfully tested on Linux and MacOSX using g++ (>=4.6), clang++ (>=3.2), and icc (>=14.0).
libpca requires Armadillo (>=3.2.4) which can be obtained as a pre-compiled package on most distributions or directly from http://arma.sourceforge.net.
libpca is being developed by Christian Blume. Contact Christian at firstname.lastname@example.org for any questions or comments.
- computes a principal component analysis
- computes energy, eigenvalues, eigenvectors, principal components
- option to normalize the data matrix
- option to bootstrap the eigenproblem to obtain uncertainty estimates of energy and eigenvalues
- methods to project data records to the space of principal components and back
- method to reduce the number of eigenvectors affecting the data record projections
- methods to check the accuracy of the solution to the eigenproblem
- methods to save and load pca properties to and from files
- pca offers a standard C++ interface using not more than primitive types, std::string, and std::vector
- libpca comes with example and unit tests
- a great deal of libpca runs in parallel thanks to Armadillo
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