pyRiemann: Machine learning for multivariate data with Riemannian geometryΒΆ
pyRiemann is a Python machine learning package based on scikit-learn API. It provides a high-level interface for processing and classification of real (resp. complex)-valued multivariate data through the Riemannian geometry of symmetric (resp. Hermitian) positive definite (SPD) (resp. HPD) matrices.
For a brief introduction to the ideas behind the package, you can read the introductory notes. More practical information is on the installation page. You may also want to browse the example gallery to get a sense for what you can do with pyRiemann and API reference to find out how.
To see the code or report a bug, please visit the github repository.