Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, GNB, Ridge Regressions, Sparse Multinomial Logistic Regression), and bindings to external machine learning libraries (libsvm, shogun).
While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it is eminently suited for such datasets.
Homepage: http://www.pymvpa.org
Associated blends:
The repository contains binary packages for the following distribution releases and system architectures. The corresponding source packages are available too.
Note
Do not download this package manually if you plan to use it regularly. Instead configure your package manager to use this repository by following the instructions on the front page.
See also
Original Maintainer: Experimental Psychology Maintainers <pkg-exppsy-maintainers@lists.alioth.debian.org>
(if there is any chance that some problem is specific to the package distributed through the NeuroDebian repository, please contact pkg-exppsy-maintainers@lists.alioth.debian.org instead of the original maintainer)
See also
See also