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Analyzed 21 days ago. based on code collected about 2 months ago.

Project Summary

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, Ridge Regressions, Sparse Multinomial Logistic Regression, GPR. RFE, I-RELIEF), and bindings to external ML libraries (libsvm, shogun, R). While it is not limited to neuroimaging data (e.g. FMRI) it is eminently suited for such datasets.

In a Nutshell, PyMVPA...

This Project has No vulnerabilities Reported Against it

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7 Other

30 Day Summary

Aug 4 2016 — Sep 3 2016

12 Month Summary

Sep 3 2015 — Sep 3 2016
  • 218 Commits
    Down -287 (56%) from previous 12 months
  • 6 Contributors
    Down -8 (57%) from previous 12 months