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PyMVPA eases statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. It is designed to integrate well with related software packages, such as scikit-learn, shogun, and MDP.
CoSMoMVPA provides univariate and multivariate analyses for large datasets in the Matlab / GNU Octave language. It supports a uniform data structure with support for cross validation, classification, similarity measures, data-driven information mapping, and chance capitalization correction.